Merge branch 'dev' into add-vercel-react-best-practices-skill

### Changes 🏗️

- Added a placeholder UI for Google Drive Picker in INPUT block type
- Improved detection of Google Drive file objects in schema validation
- Extracted `isGoogleDrivePickerSchema` function for better code
organization
- Added spacing between array field elements with a gap-2 class
- Added debug logging for preprocessed schema in FormRenderer

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Verified Google Drive Picker shows placeholder in INPUT blocks
  - [x] Confirmed array field elements have proper spacing
  - [x] Tested that Google Drive file objects are properly detected

.branchlet.json

@@ -0,0 +1,37 @@
+{
+  "worktreeCopyPatterns": [
+    ".env*",
+    ".vscode/**",
+    ".auth/**",
+    ".claude/**",
+    "autogpt_platform/.env*",
+    "autogpt_platform/backend/.env*",
+    "autogpt_platform/frontend/.env*",
+    "autogpt_platform/frontend/.auth/**",
+    "autogpt_platform/db/docker/.env*"
+  ],
+  "worktreeCopyIgnores": [
+    "**/node_modules/**",
+    "**/dist/**",
+    "**/.git/**",
+    "**/Thumbs.db",
+    "**/.DS_Store",
+    "**/.next/**",
+    "**/__pycache__/**",
+    "**/.ruff_cache/**",
+    "**/.pytest_cache/**",
+    "**/*.pyc",
+    "**/playwright-report/**",
+    "**/logs/**",
+    "**/site/**"
+  ],
+  "worktreePathTemplate": "$BASE_PATH.worktree",
+  "postCreateCmd": [
+    "cd autogpt_platform/autogpt_libs && poetry install",
+    "cd autogpt_platform/backend && poetry install && poetry run prisma generate",
+    "cd autogpt_platform/frontend && pnpm install",
+    "cd docs && pip install -r requirements.txt"
+  ],
+  "terminalCommand": "code .",
+  "deleteBranchWithWorktree": false
+}

.claude/skills/vercel-react-best-practices/SKILL.md

@@ -0,0 +1,125 @@
+---
+name: vercel-react-best-practices
+description: React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
+license: MIT
+metadata:
+  author: vercel
+  version: "1.0.0"
+---
+
+# Vercel React Best Practices
+
+Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Contains 45 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.
+
+## When to Apply
+
+Reference these guidelines when:
+- Writing new React components or Next.js pages
+- Implementing data fetching (client or server-side)
+- Reviewing code for performance issues
+- Refactoring existing React/Next.js code
+- Optimizing bundle size or load times
+
+## Rule Categories by Priority
+
+| Priority | Category | Impact | Prefix |
+|----------|----------|--------|--------|
+| 1 | Eliminating Waterfalls | CRITICAL | `async-` |
+| 2 | Bundle Size Optimization | CRITICAL | `bundle-` |
+| 3 | Server-Side Performance | HIGH | `server-` |
+| 4 | Client-Side Data Fetching | MEDIUM-HIGH | `client-` |
+| 5 | Re-render Optimization | MEDIUM | `rerender-` |
+| 6 | Rendering Performance | MEDIUM | `rendering-` |
+| 7 | JavaScript Performance | LOW-MEDIUM | `js-` |
+| 8 | Advanced Patterns | LOW | `advanced-` |
+
+## Quick Reference
+
+### 1. Eliminating Waterfalls (CRITICAL)
+
+- `async-defer-await` - Move await into branches where actually used
+- `async-parallel` - Use Promise.all() for independent operations
+- `async-dependencies` - Use better-all for partial dependencies
+- `async-api-routes` - Start promises early, await late in API routes
+- `async-suspense-boundaries` - Use Suspense to stream content
+
+### 2. Bundle Size Optimization (CRITICAL)
+
+- `bundle-barrel-imports` - Import directly, avoid barrel files
+- `bundle-dynamic-imports` - Use next/dynamic for heavy components
+- `bundle-defer-third-party` - Load analytics/logging after hydration
+- `bundle-conditional` - Load modules only when feature is activated
+- `bundle-preload` - Preload on hover/focus for perceived speed
+
+### 3. Server-Side Performance (HIGH)
+
+- `server-cache-react` - Use React.cache() for per-request deduplication
+- `server-cache-lru` - Use LRU cache for cross-request caching
+- `server-serialization` - Minimize data passed to client components
+- `server-parallel-fetching` - Restructure components to parallelize fetches
+- `server-after-nonblocking` - Use after() for non-blocking operations
+
+### 4. Client-Side Data Fetching (MEDIUM-HIGH)
+
+- `client-swr-dedup` - Use SWR for automatic request deduplication
+- `client-event-listeners` - Deduplicate global event listeners
+
+### 5. Re-render Optimization (MEDIUM)
+
+- `rerender-defer-reads` - Don't subscribe to state only used in callbacks
+- `rerender-memo` - Extract expensive work into memoized components
+- `rerender-dependencies` - Use primitive dependencies in effects
+- `rerender-derived-state` - Subscribe to derived booleans, not raw values
+- `rerender-functional-setstate` - Use functional setState for stable callbacks
+- `rerender-lazy-state-init` - Pass function to useState for expensive values
+- `rerender-transitions` - Use startTransition for non-urgent updates
+
+### 6. Rendering Performance (MEDIUM)
+
+- `rendering-animate-svg-wrapper` - Animate div wrapper, not SVG element
+- `rendering-content-visibility` - Use content-visibility for long lists
+- `rendering-hoist-jsx` - Extract static JSX outside components
+- `rendering-svg-precision` - Reduce SVG coordinate precision
+- `rendering-hydration-no-flicker` - Use inline script for client-only data
+- `rendering-activity` - Use Activity component for show/hide
+- `rendering-conditional-render` - Use ternary, not && for conditionals
+
+### 7. JavaScript Performance (LOW-MEDIUM)
+
+- `js-batch-dom-css` - Group CSS changes via classes or cssText
+- `js-index-maps` - Build Map for repeated lookups
+- `js-cache-property-access` - Cache object properties in loops
+- `js-cache-function-results` - Cache function results in module-level Map
+- `js-cache-storage` - Cache localStorage/sessionStorage reads
+- `js-combine-iterations` - Combine multiple filter/map into one loop
+- `js-length-check-first` - Check array length before expensive comparison
+- `js-early-exit` - Return early from functions
+- `js-hoist-regexp` - Hoist RegExp creation outside loops
+- `js-min-max-loop` - Use loop for min/max instead of sort
+- `js-set-map-lookups` - Use Set/Map for O(1) lookups
+- `js-tosorted-immutable` - Use toSorted() for immutability
+
+### 8. Advanced Patterns (LOW)
+
+- `advanced-event-handler-refs` - Store event handlers in refs
+- `advanced-use-latest` - useLatest for stable callback refs
+
+## How to Use
+
+Read individual rule files for detailed explanations and code examples:
+
+```
+rules/async-parallel.md
+rules/bundle-barrel-imports.md
+rules/_sections.md
+```
+
+Each rule file contains:
+- Brief explanation of why it matters
+- Incorrect code example with explanation
+- Correct code example with explanation
+- Additional context and references
+
+## Full Compiled Document
+
+For the complete guide with all rules expanded: `AGENTS.md`

.claude/skills/vercel-react-best-practices/rules/advanced-event-handler-refs.md

@@ -0,0 +1,55 @@
+---
+title: Store Event Handlers in Refs
+impact: LOW
+impactDescription: stable subscriptions
+tags: advanced, hooks, refs, event-handlers, optimization
+---
+
+## Store Event Handlers in Refs
+
+Store callbacks in refs when used in effects that shouldn't re-subscribe on callback changes.
+
+**Incorrect (re-subscribes on every render):**
+
+```tsx
+function useWindowEvent(event: string, handler: () => void) {
+  useEffect(() => {
+    window.addEventListener(event, handler)
+    return () => window.removeEventListener(event, handler)
+  }, [event, handler])
+}
+```
+
+**Correct (stable subscription):**
+
+```tsx
+function useWindowEvent(event: string, handler: () => void) {
+  const handlerRef = useRef(handler)
+  useEffect(() => {
+    handlerRef.current = handler
+  }, [handler])
+
+  useEffect(() => {
+    const listener = () => handlerRef.current()
+    window.addEventListener(event, listener)
+    return () => window.removeEventListener(event, listener)
+  }, [event])
+}
+```
+
+**Alternative: use `useEffectEvent` if you're on latest React:**
+
+```tsx
+import { useEffectEvent } from 'react'
+
+function useWindowEvent(event: string, handler: () => void) {
+  const onEvent = useEffectEvent(handler)
+
+  useEffect(() => {
+    window.addEventListener(event, onEvent)
+    return () => window.removeEventListener(event, onEvent)
+  }, [event])
+}
+```
+
+`useEffectEvent` provides a cleaner API for the same pattern: it creates a stable function reference that always calls the latest version of the handler.

.claude/skills/vercel-react-best-practices/rules/advanced-use-latest.md

@@ -0,0 +1,49 @@
+---
+title: useLatest for Stable Callback Refs
+impact: LOW
+impactDescription: prevents effect re-runs
+tags: advanced, hooks, useLatest, refs, optimization
+---
+
+## useLatest for Stable Callback Refs
+
+Access latest values in callbacks without adding them to dependency arrays. Prevents effect re-runs while avoiding stale closures.
+
+**Implementation:**
+
+```typescript
+function useLatest<T>(value: T) {
+  const ref = useRef(value)
+  useEffect(() => {
+    ref.current = value
+  }, [value])
+  return ref
+}
+```
+
+**Incorrect (effect re-runs on every callback change):**
+
+```tsx
+function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
+  const [query, setQuery] = useState('')
+
+  useEffect(() => {
+    const timeout = setTimeout(() => onSearch(query), 300)
+    return () => clearTimeout(timeout)
+  }, [query, onSearch])
+}
+```
+
+**Correct (stable effect, fresh callback):**
+
+```tsx
+function SearchInput({ onSearch }: { onSearch: (q: string) => void }) {
+  const [query, setQuery] = useState('')
+  const onSearchRef = useLatest(onSearch)
+
+  useEffect(() => {
+    const timeout = setTimeout(() => onSearchRef.current(query), 300)
+    return () => clearTimeout(timeout)
+  }, [query])
+}
+```

.claude/skills/vercel-react-best-practices/rules/async-api-routes.md

@@ -0,0 +1,38 @@
+---
+title: Prevent Waterfall Chains in API Routes
+impact: CRITICAL
+impactDescription: 2-10× improvement
+tags: api-routes, server-actions, waterfalls, parallelization
+---
+
+## Prevent Waterfall Chains in API Routes
+
+In API routes and Server Actions, start independent operations immediately, even if you don't await them yet.
+
+**Incorrect (config waits for auth, data waits for both):**
+
+```typescript
+export async function GET(request: Request) {
+  const session = await auth()
+  const config = await fetchConfig()
+  const data = await fetchData(session.user.id)
+  return Response.json({ data, config })
+}
+```
+
+**Correct (auth and config start immediately):**
+
+```typescript
+export async function GET(request: Request) {
+  const sessionPromise = auth()
+  const configPromise = fetchConfig()
+  const session = await sessionPromise
+  const [config, data] = await Promise.all([
+    configPromise,
+    fetchData(session.user.id)
+  ])
+  return Response.json({ data, config })
+}
+```
+
+For operations with more complex dependency chains, use `better-all` to automatically maximize parallelism (see Dependency-Based Parallelization).

.claude/skills/vercel-react-best-practices/rules/async-defer-await.md

@@ -0,0 +1,80 @@
+---
+title: Defer Await Until Needed
+impact: HIGH
+impactDescription: avoids blocking unused code paths
+tags: async, await, conditional, optimization
+---
+
+## Defer Await Until Needed
+
+Move `await` operations into the branches where they're actually used to avoid blocking code paths that don't need them.
+
+**Incorrect (blocks both branches):**
+
+```typescript
+async function handleRequest(userId: string, skipProcessing: boolean) {
+  const userData = await fetchUserData(userId)
+  
+  if (skipProcessing) {
+    // Returns immediately but still waited for userData
+    return { skipped: true }
+  }
+  
+  // Only this branch uses userData
+  return processUserData(userData)
+}
+```
+
+**Correct (only blocks when needed):**
+
+```typescript
+async function handleRequest(userId: string, skipProcessing: boolean) {
+  if (skipProcessing) {
+    // Returns immediately without waiting
+    return { skipped: true }
+  }
+  
+  // Fetch only when needed
+  const userData = await fetchUserData(userId)
+  return processUserData(userData)
+}
+```
+
+**Another example (early return optimization):**
+
+```typescript
+// Incorrect: always fetches permissions
+async function updateResource(resourceId: string, userId: string) {
+  const permissions = await fetchPermissions(userId)
+  const resource = await getResource(resourceId)
+  
+  if (!resource) {
+    return { error: 'Not found' }
+  }
+  
+  if (!permissions.canEdit) {
+    return { error: 'Forbidden' }
+  }
+  
+  return await updateResourceData(resource, permissions)
+}
+
+// Correct: fetches only when needed
+async function updateResource(resourceId: string, userId: string) {
+  const resource = await getResource(resourceId)
+  
+  if (!resource) {
+    return { error: 'Not found' }
+  }
+  
+  const permissions = await fetchPermissions(userId)
+  
+  if (!permissions.canEdit) {
+    return { error: 'Forbidden' }
+  }
+  
+  return await updateResourceData(resource, permissions)
+}
+```
+
+This optimization is especially valuable when the skipped branch is frequently taken, or when the deferred operation is expensive.

.claude/skills/vercel-react-best-practices/rules/async-dependencies.md

@@ -0,0 +1,36 @@
+---
+title: Dependency-Based Parallelization
+impact: CRITICAL
+impactDescription: 2-10× improvement
+tags: async, parallelization, dependencies, better-all
+---
+
+## Dependency-Based Parallelization
+
+For operations with partial dependencies, use `better-all` to maximize parallelism. It automatically starts each task at the earliest possible moment.
+
+**Incorrect (profile waits for config unnecessarily):**
+
+```typescript
+const [user, config] = await Promise.all([
+  fetchUser(),
+  fetchConfig()
+])
+const profile = await fetchProfile(user.id)
+```
+
+**Correct (config and profile run in parallel):**
+
+```typescript
+import { all } from 'better-all'
+
+const { user, config, profile } = await all({
+  async user() { return fetchUser() },
+  async config() { return fetchConfig() },
+  async profile() {
+    return fetchProfile((await this.$.user).id)
+  }
+})
+```
+
+Reference: [https://github.com/shuding/better-all](https://github.com/shuding/better-all)

.claude/skills/vercel-react-best-practices/rules/async-parallel.md

@@ -0,0 +1,28 @@
+---
+title: Promise.all() for Independent Operations
+impact: CRITICAL
+impactDescription: 2-10× improvement
+tags: async, parallelization, promises, waterfalls
+---
+
+## Promise.all() for Independent Operations
+
+When async operations have no interdependencies, execute them concurrently using `Promise.all()`.
+
+**Incorrect (sequential execution, 3 round trips):**
+
+```typescript
+const user = await fetchUser()
+const posts = await fetchPosts()
+const comments = await fetchComments()
+```
+
+**Correct (parallel execution, 1 round trip):**
+
+```typescript
+const [user, posts, comments] = await Promise.all([
+  fetchUser(),
+  fetchPosts(),
+  fetchComments()
+])
+```

.claude/skills/vercel-react-best-practices/rules/async-suspense-boundaries.md

@@ -0,0 +1,99 @@
+---
+title: Strategic Suspense Boundaries
+impact: HIGH
+impactDescription: faster initial paint
+tags: async, suspense, streaming, layout-shift
+---
+
+## Strategic Suspense Boundaries
+
+Instead of awaiting data in async components before returning JSX, use Suspense boundaries to show the wrapper UI faster while data loads.
+
+**Incorrect (wrapper blocked by data fetching):**
+
+```tsx
+async function Page() {
+  const data = await fetchData() // Blocks entire page
+  
+  return (
+    <div>
+      <div>Sidebar</div>
+      <div>Header</div>
+      <div>
+        <DataDisplay data={data} />
+      </div>
+      <div>Footer</div>
+    </div>
+  )
+}
+```
+
+The entire layout waits for data even though only the middle section needs it.
+
+**Correct (wrapper shows immediately, data streams in):**
+
+```tsx
+function Page() {
+  return (
+    <div>
+      <div>Sidebar</div>
+      <div>Header</div>
+      <div>
+        <Suspense fallback={<Skeleton />}>
+          <DataDisplay />
+        </Suspense>
+      </div>
+      <div>Footer</div>
+    </div>
+  )
+}
+
+async function DataDisplay() {
+  const data = await fetchData() // Only blocks this component
+  return <div>{data.content}</div>
+}
+```
+
+Sidebar, Header, and Footer render immediately. Only DataDisplay waits for data.
+
+**Alternative (share promise across components):**
+
+```tsx
+function Page() {
+  // Start fetch immediately, but don't await
+  const dataPromise = fetchData()
+  
+  return (
+    <div>
+      <div>Sidebar</div>
+      <div>Header</div>
+      <Suspense fallback={<Skeleton />}>
+        <DataDisplay dataPromise={dataPromise} />
+        <DataSummary dataPromise={dataPromise} />
+      </Suspense>
+      <div>Footer</div>
+    </div>
+  )
+}
+
+function DataDisplay({ dataPromise }: { dataPromise: Promise<Data> }) {
+  const data = use(dataPromise) // Unwraps the promise
+  return <div>{data.content}</div>
+}
+
+function DataSummary({ dataPromise }: { dataPromise: Promise<Data> }) {
+  const data = use(dataPromise) // Reuses the same promise
+  return <div>{data.summary}</div>
+}
+```
+
+Both components share the same promise, so only one fetch occurs. Layout renders immediately while both components wait together.
+
+**When NOT to use this pattern:**
+
+- Critical data needed for layout decisions (affects positioning)
+- SEO-critical content above the fold
+- Small, fast queries where suspense overhead isn't worth it
+- When you want to avoid layout shift (loading → content jump)
+
+**Trade-off:** Faster initial paint vs potential layout shift. Choose based on your UX priorities.

.claude/skills/vercel-react-best-practices/rules/bundle-barrel-imports.md

@@ -0,0 +1,59 @@
+---
+title: Avoid Barrel File Imports
+impact: CRITICAL
+impactDescription: 200-800ms import cost, slow builds
+tags: bundle, imports, tree-shaking, barrel-files, performance
+---
+
+## Avoid Barrel File Imports
+
+Import directly from source files instead of barrel files to avoid loading thousands of unused modules. **Barrel files** are entry points that re-export multiple modules (e.g., `index.js` that does `export * from './module'`).
+
+Popular icon and component libraries can have **up to 10,000 re-exports** in their entry file. For many React packages, **it takes 200-800ms just to import them**, affecting both development speed and production cold starts.
+
+**Why tree-shaking doesn't help:** When a library is marked as external (not bundled), the bundler can't optimize it. If you bundle it to enable tree-shaking, builds become substantially slower analyzing the entire module graph.
+
+**Incorrect (imports entire library):**
+
+```tsx
+import { Check, X, Menu } from 'lucide-react'
+// Loads 1,583 modules, takes ~2.8s extra in dev
+// Runtime cost: 200-800ms on every cold start
+
+import { Button, TextField } from '@mui/material'
+// Loads 2,225 modules, takes ~4.2s extra in dev
+```
+
+**Correct (imports only what you need):**
+
+```tsx
+import Check from 'lucide-react/dist/esm/icons/check'
+import X from 'lucide-react/dist/esm/icons/x'
+import Menu from 'lucide-react/dist/esm/icons/menu'
+// Loads only 3 modules (~2KB vs ~1MB)
+
+import Button from '@mui/material/Button'
+import TextField from '@mui/material/TextField'
+// Loads only what you use
+```
+
+**Alternative (Next.js 13.5+):**
+
+```js
+// next.config.js - use optimizePackageImports
+module.exports = {
+  experimental: {
+    optimizePackageImports: ['lucide-react', '@mui/material']
+  }
+}
+
+// Then you can keep the ergonomic barrel imports:
+import { Check, X, Menu } from 'lucide-react'
+// Automatically transformed to direct imports at build time
+```
+
+Direct imports provide 15-70% faster dev boot, 28% faster builds, 40% faster cold starts, and significantly faster HMR.
+
+Libraries commonly affected: `lucide-react`, `@mui/material`, `@mui/icons-material`, `@tabler/icons-react`, `react-icons`, `@headlessui/react`, `@radix-ui/react-*`, `lodash`, `ramda`, `date-fns`, `rxjs`, `react-use`.
+
+Reference: [How we optimized package imports in Next.js](https://vercel.com/blog/how-we-optimized-package-imports-in-next-js)

.claude/skills/vercel-react-best-practices/rules/bundle-conditional.md

@@ -0,0 +1,31 @@
+---
+title: Conditional Module Loading
+impact: HIGH
+impactDescription: loads large data only when needed
+tags: bundle, conditional-loading, lazy-loading
+---
+
+## Conditional Module Loading
+
+Load large data or modules only when a feature is activated.
+
+**Example (lazy-load animation frames):**
+
+```tsx
+function AnimationPlayer({ enabled }: { enabled: boolean }) {
+  const [frames, setFrames] = useState<Frame[] | null>(null)
+
+  useEffect(() => {
+    if (enabled && !frames && typeof window !== 'undefined') {
+      import('./animation-frames.js')
+        .then(mod => setFrames(mod.frames))
+        .catch(() => setEnabled(false))
+    }
+  }, [enabled, frames])
+
+  if (!frames) return <Skeleton />
+  return <Canvas frames={frames} />
+}
+```
+
+The `typeof window !== 'undefined'` check prevents bundling this module for SSR, optimizing server bundle size and build speed.

.claude/skills/vercel-react-best-practices/rules/bundle-defer-third-party.md

@@ -0,0 +1,49 @@
+---
+title: Defer Non-Critical Third-Party Libraries
+impact: MEDIUM
+impactDescription: loads after hydration
+tags: bundle, third-party, analytics, defer
+---
+
+## Defer Non-Critical Third-Party Libraries
+
+Analytics, logging, and error tracking don't block user interaction. Load them after hydration.
+
+**Incorrect (blocks initial bundle):**
+
+```tsx
+import { Analytics } from '@vercel/analytics/react'
+
+export default function RootLayout({ children }) {
+  return (
+    <html>
+      <body>
+        {children}
+        <Analytics />
+      </body>
+    </html>
+  )
+}
+```
+
+**Correct (loads after hydration):**
+
+```tsx
+import dynamic from 'next/dynamic'
+
+const Analytics = dynamic(
+  () => import('@vercel/analytics/react').then(m => m.Analytics),
+  { ssr: false }
+)
+
+export default function RootLayout({ children }) {
+  return (
+    <html>
+      <body>
+        {children}
+        <Analytics />
+      </body>
+    </html>
+  )
+}
+```

.claude/skills/vercel-react-best-practices/rules/bundle-dynamic-imports.md

@@ -0,0 +1,35 @@
+---
+title: Dynamic Imports for Heavy Components
+impact: CRITICAL
+impactDescription: directly affects TTI and LCP
+tags: bundle, dynamic-import, code-splitting, next-dynamic
+---
+
+## Dynamic Imports for Heavy Components
+
+Use `next/dynamic` to lazy-load large components not needed on initial render.
+
+**Incorrect (Monaco bundles with main chunk ~300KB):**
+
+```tsx
+import { MonacoEditor } from './monaco-editor'
+
+function CodePanel({ code }: { code: string }) {
+  return <MonacoEditor value={code} />
+}
+```
+
+**Correct (Monaco loads on demand):**
+
+```tsx
+import dynamic from 'next/dynamic'
+
+const MonacoEditor = dynamic(
+  () => import('./monaco-editor').then(m => m.MonacoEditor),
+  { ssr: false }
+)
+
+function CodePanel({ code }: { code: string }) {
+  return <MonacoEditor value={code} />
+}
+```

.claude/skills/vercel-react-best-practices/rules/bundle-preload.md

@@ -0,0 +1,50 @@
+---
+title: Preload Based on User Intent
+impact: MEDIUM
+impactDescription: reduces perceived latency
+tags: bundle, preload, user-intent, hover
+---
+
+## Preload Based on User Intent
+
+Preload heavy bundles before they're needed to reduce perceived latency.
+
+**Example (preload on hover/focus):**
+
+```tsx
+function EditorButton({ onClick }: { onClick: () => void }) {
+  const preload = () => {
+    if (typeof window !== 'undefined') {
+      void import('./monaco-editor')
+    }
+  }
+
+  return (
+    <button
+      onMouseEnter={preload}
+      onFocus={preload}
+      onClick={onClick}
+    >
+      Open Editor
+    </button>
+  )
+}
+```
+
+**Example (preload when feature flag is enabled):**
+
+```tsx
+function FlagsProvider({ children, flags }: Props) {
+  useEffect(() => {
+    if (flags.editorEnabled && typeof window !== 'undefined') {
+      void import('./monaco-editor').then(mod => mod.init())
+    }
+  }, [flags.editorEnabled])
+
+  return <FlagsContext.Provider value={flags}>
+    {children}
+  </FlagsContext.Provider>
+}
+```
+
+The `typeof window !== 'undefined'` check prevents bundling preloaded modules for SSR, optimizing server bundle size and build speed.

.claude/skills/vercel-react-best-practices/rules/client-event-listeners.md

@@ -0,0 +1,74 @@
+---
+title: Deduplicate Global Event Listeners
+impact: LOW
+impactDescription: single listener for N components
+tags: client, swr, event-listeners, subscription
+---
+
+## Deduplicate Global Event Listeners
+
+Use `useSWRSubscription()` to share global event listeners across component instances.
+
+**Incorrect (N instances = N listeners):**
+
+```tsx
+function useKeyboardShortcut(key: string, callback: () => void) {
+  useEffect(() => {
+    const handler = (e: KeyboardEvent) => {
+      if (e.metaKey && e.key === key) {
+        callback()
+      }
+    }
+    window.addEventListener('keydown', handler)
+    return () => window.removeEventListener('keydown', handler)
+  }, [key, callback])
+}
+```
+
+When using the `useKeyboardShortcut` hook multiple times, each instance will register a new listener.
+
+**Correct (N instances = 1 listener):**
+
+```tsx
+import useSWRSubscription from 'swr/subscription'
+
+// Module-level Map to track callbacks per key
+const keyCallbacks = new Map<string, Set<() => void>>()
+
+function useKeyboardShortcut(key: string, callback: () => void) {
+  // Register this callback in the Map
+  useEffect(() => {
+    if (!keyCallbacks.has(key)) {
+      keyCallbacks.set(key, new Set())
+    }
+    keyCallbacks.get(key)!.add(callback)
+
+    return () => {
+      const set = keyCallbacks.get(key)
+      if (set) {
+        set.delete(callback)
+        if (set.size === 0) {
+          keyCallbacks.delete(key)
+        }
+      }
+    }
+  }, [key, callback])
+
+  useSWRSubscription('global-keydown', () => {
+    const handler = (e: KeyboardEvent) => {
+      if (e.metaKey && keyCallbacks.has(e.key)) {
+        keyCallbacks.get(e.key)!.forEach(cb => cb())
+      }
+    }
+    window.addEventListener('keydown', handler)
+    return () => window.removeEventListener('keydown', handler)
+  })
+}
+
+function Profile() {
+  // Multiple shortcuts will share the same listener
+  useKeyboardShortcut('p', () => { /* ... */ }) 
+  useKeyboardShortcut('k', () => { /* ... */ })
+  // ...
+}
+```

.claude/skills/vercel-react-best-practices/rules/client-swr-dedup.md

@@ -0,0 +1,56 @@
+---
+title: Use SWR for Automatic Deduplication
+impact: MEDIUM-HIGH
+impactDescription: automatic deduplication
+tags: client, swr, deduplication, data-fetching
+---
+
+## Use SWR for Automatic Deduplication
+
+SWR enables request deduplication, caching, and revalidation across component instances.
+
+**Incorrect (no deduplication, each instance fetches):**
+
+```tsx
+function UserList() {
+  const [users, setUsers] = useState([])
+  useEffect(() => {
+    fetch('/api/users')
+      .then(r => r.json())
+      .then(setUsers)
+  }, [])
+}
+```
+
+**Correct (multiple instances share one request):**
+
+```tsx
+import useSWR from 'swr'
+
+function UserList() {
+  const { data: users } = useSWR('/api/users', fetcher)
+}
+```
+
+**For immutable data:**
+
+```tsx
+import { useImmutableSWR } from '@/lib/swr'
+
+function StaticContent() {
+  const { data } = useImmutableSWR('/api/config', fetcher)
+}
+```
+
+**For mutations:**
+
+```tsx
+import { useSWRMutation } from 'swr/mutation'
+
+function UpdateButton() {
+  const { trigger } = useSWRMutation('/api/user', updateUser)
+  return <button onClick={() => trigger()}>Update</button>
+}
+```
+
+Reference: [https://swr.vercel.app](https://swr.vercel.app)

.claude/skills/vercel-react-best-practices/rules/js-batch-dom-css.md

@@ -0,0 +1,82 @@
+---
+title: Batch DOM CSS Changes
+impact: MEDIUM
+impactDescription: reduces reflows/repaints
+tags: javascript, dom, css, performance, reflow
+---
+
+## Batch DOM CSS Changes
+
+Avoid changing styles one property at a time. Group multiple CSS changes together via classes or `cssText` to minimize browser reflows.
+
+**Incorrect (multiple reflows):**
+
+```typescript
+function updateElementStyles(element: HTMLElement) {
+  // Each line triggers a reflow
+  element.style.width = '100px'
+  element.style.height = '200px'
+  element.style.backgroundColor = 'blue'
+  element.style.border = '1px solid black'
+}
+```
+
+**Correct (add class - single reflow):**
+
+```typescript
+// CSS file
+.highlighted-box {
+  width: 100px;
+  height: 200px;
+  background-color: blue;
+  border: 1px solid black;
+}
+
+// JavaScript
+function updateElementStyles(element: HTMLElement) {
+  element.classList.add('highlighted-box')
+}
+```
+
+**Correct (change cssText - single reflow):**
+
+```typescript
+function updateElementStyles(element: HTMLElement) {
+  element.style.cssText = `
+    width: 100px;
+    height: 200px;
+    background-color: blue;
+    border: 1px solid black;
+  `
+}
+```
+
+**React example:**
+
+```tsx
+// Incorrect: changing styles one by one
+function Box({ isHighlighted }: { isHighlighted: boolean }) {
+  const ref = useRef<HTMLDivElement>(null)
+  
+  useEffect(() => {
+    if (ref.current && isHighlighted) {
+      ref.current.style.width = '100px'
+      ref.current.style.height = '200px'
+      ref.current.style.backgroundColor = 'blue'
+    }
+  }, [isHighlighted])
+  
+  return <div ref={ref}>Content</div>
+}
+
+// Correct: toggle class
+function Box({ isHighlighted }: { isHighlighted: boolean }) {
+  return (
+    <div className={isHighlighted ? 'highlighted-box' : ''}>
+      Content
+    </div>
+  )
+}
+```
+
+Prefer CSS classes over inline styles when possible. Classes are cached by the browser and provide better separation of concerns.

.claude/skills/vercel-react-best-practices/rules/js-cache-function-results.md

@@ -0,0 +1,80 @@
+---
+title: Cache Repeated Function Calls
+impact: MEDIUM
+impactDescription: avoid redundant computation
+tags: javascript, cache, memoization, performance
+---
+
+## Cache Repeated Function Calls
+
+Use a module-level Map to cache function results when the same function is called repeatedly with the same inputs during render.
+
+**Incorrect (redundant computation):**
+
+```typescript
+function ProjectList({ projects }: { projects: Project[] }) {
+  return (
+    <div>
+      {projects.map(project => {
+        // slugify() called 100+ times for same project names
+        const slug = slugify(project.name)
+        
+        return <ProjectCard key={project.id} slug={slug} />
+      })}
+    </div>
+  )
+}
+```
+
+**Correct (cached results):**
+
+```typescript
+// Module-level cache
+const slugifyCache = new Map<string, string>()
+
+function cachedSlugify(text: string): string {
+  if (slugifyCache.has(text)) {
+    return slugifyCache.get(text)!
+  }
+  const result = slugify(text)
+  slugifyCache.set(text, result)
+  return result
+}
+
+function ProjectList({ projects }: { projects: Project[] }) {
+  return (
+    <div>
+      {projects.map(project => {
+        // Computed only once per unique project name
+        const slug = cachedSlugify(project.name)
+        
+        return <ProjectCard key={project.id} slug={slug} />
+      })}
+    </div>
+  )
+}
+```
+
+**Simpler pattern for single-value functions:**
+
+```typescript
+let isLoggedInCache: boolean | null = null
+
+function isLoggedIn(): boolean {
+  if (isLoggedInCache !== null) {
+    return isLoggedInCache
+  }
+  
+  isLoggedInCache = document.cookie.includes('auth=')
+  return isLoggedInCache
+}
+
+// Clear cache when auth changes
+function onAuthChange() {
+  isLoggedInCache = null
+}
+```
+
+Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
+
+Reference: [How we made the Vercel Dashboard twice as fast](https://vercel.com/blog/how-we-made-the-vercel-dashboard-twice-as-fast)

.claude/skills/vercel-react-best-practices/rules/js-cache-property-access.md

@@ -0,0 +1,28 @@
+---
+title: Cache Property Access in Loops
+impact: LOW-MEDIUM
+impactDescription: reduces lookups
+tags: javascript, loops, optimization, caching
+---
+
+## Cache Property Access in Loops
+
+Cache object property lookups in hot paths.
+
+**Incorrect (3 lookups × N iterations):**
+
+```typescript
+for (let i = 0; i < arr.length; i++) {
+  process(obj.config.settings.value)
+}
+```
+
+**Correct (1 lookup total):**
+
+```typescript
+const value = obj.config.settings.value
+const len = arr.length
+for (let i = 0; i < len; i++) {
+  process(value)
+}
+```

.claude/skills/vercel-react-best-practices/rules/js-cache-storage.md

@@ -0,0 +1,70 @@
+---
+title: Cache Storage API Calls
+impact: LOW-MEDIUM
+impactDescription: reduces expensive I/O
+tags: javascript, localStorage, storage, caching, performance
+---
+
+## Cache Storage API Calls
+
+`localStorage`, `sessionStorage`, and `document.cookie` are synchronous and expensive. Cache reads in memory.
+
+**Incorrect (reads storage on every call):**
+
+```typescript
+function getTheme() {
+  return localStorage.getItem('theme') ?? 'light'
+}
+// Called 10 times = 10 storage reads
+```
+
+**Correct (Map cache):**
+
+```typescript
+const storageCache = new Map<string, string | null>()
+
+function getLocalStorage(key: string) {
+  if (!storageCache.has(key)) {
+    storageCache.set(key, localStorage.getItem(key))
+  }
+  return storageCache.get(key)
+}
+
+function setLocalStorage(key: string, value: string) {
+  localStorage.setItem(key, value)
+  storageCache.set(key, value)  // keep cache in sync
+}
+```
+
+Use a Map (not a hook) so it works everywhere: utilities, event handlers, not just React components.
+
+**Cookie caching:**
+
+```typescript
+let cookieCache: Record<string, string> | null = null
+
+function getCookie(name: string) {
+  if (!cookieCache) {
+    cookieCache = Object.fromEntries(
+      document.cookie.split('; ').map(c => c.split('='))
+    )
+  }
+  return cookieCache[name]
+}
+```
+
+**Important (invalidate on external changes):**
+
+If storage can change externally (another tab, server-set cookies), invalidate cache:
+
+```typescript
+window.addEventListener('storage', (e) => {
+  if (e.key) storageCache.delete(e.key)
+})
+
+document.addEventListener('visibilitychange', () => {
+  if (document.visibilityState === 'visible') {
+    storageCache.clear()
+  }
+})
+```

.claude/skills/vercel-react-best-practices/rules/js-combine-iterations.md

@@ -0,0 +1,32 @@
+---
+title: Combine Multiple Array Iterations
+impact: LOW-MEDIUM
+impactDescription: reduces iterations
+tags: javascript, arrays, loops, performance
+---
+
+## Combine Multiple Array Iterations
+
+Multiple `.filter()` or `.map()` calls iterate the array multiple times. Combine into one loop.
+
+**Incorrect (3 iterations):**
+
+```typescript
+const admins = users.filter(u => u.isAdmin)
+const testers = users.filter(u => u.isTester)
+const inactive = users.filter(u => !u.isActive)
+```
+
+**Correct (1 iteration):**
+
+```typescript
+const admins: User[] = []
+const testers: User[] = []
+const inactive: User[] = []
+
+for (const user of users) {
+  if (user.isAdmin) admins.push(user)
+  if (user.isTester) testers.push(user)
+  if (!user.isActive) inactive.push(user)
+}
+```

.claude/skills/vercel-react-best-practices/rules/js-early-exit.md

@@ -0,0 +1,50 @@
+---
+title: Early Return from Functions
+impact: LOW-MEDIUM
+impactDescription: avoids unnecessary computation
+tags: javascript, functions, optimization, early-return
+---
+
+## Early Return from Functions
+
+Return early when result is determined to skip unnecessary processing.
+
+**Incorrect (processes all items even after finding answer):**
+
+```typescript
+function validateUsers(users: User[]) {
+  let hasError = false
+  let errorMessage = ''
+  
+  for (const user of users) {
+    if (!user.email) {
+      hasError = true
+      errorMessage = 'Email required'
+    }
+    if (!user.name) {
+      hasError = true
+      errorMessage = 'Name required'
+    }
+    // Continues checking all users even after error found
+  }
+  
+  return hasError ? { valid: false, error: errorMessage } : { valid: true }
+}
+```
+
+**Correct (returns immediately on first error):**
+
+```typescript
+function validateUsers(users: User[]) {
+  for (const user of users) {
+    if (!user.email) {
+      return { valid: false, error: 'Email required' }
+    }
+    if (!user.name) {
+      return { valid: false, error: 'Name required' }
+    }
+  }
+
+  return { valid: true }
+}
+```

.claude/skills/vercel-react-best-practices/rules/js-hoist-regexp.md

@@ -0,0 +1,45 @@
+---
+title: Hoist RegExp Creation
+impact: LOW-MEDIUM
+impactDescription: avoids recreation
+tags: javascript, regexp, optimization, memoization
+---
+
+## Hoist RegExp Creation
+
+Don't create RegExp inside render. Hoist to module scope or memoize with `useMemo()`.
+
+**Incorrect (new RegExp every render):**
+
+```tsx
+function Highlighter({ text, query }: Props) {
+  const regex = new RegExp(`(${query})`, 'gi')
+  const parts = text.split(regex)
+  return <>{parts.map((part, i) => ...)}</>
+}
+```
+
+**Correct (memoize or hoist):**
+
+```tsx
+const EMAIL_REGEX = /^[^\s@]+@[^\s@]+\.[^\s@]+$/
+
+function Highlighter({ text, query }: Props) {
+  const regex = useMemo(
+    () => new RegExp(`(${escapeRegex(query)})`, 'gi'),
+    [query]
+  )
+  const parts = text.split(regex)
+  return <>{parts.map((part, i) => ...)}</>
+}
+```
+
+**Warning (global regex has mutable state):**
+
+Global regex (`/g`) has mutable `lastIndex` state:
+
+```typescript
+const regex = /foo/g
+regex.test('foo')  // true, lastIndex = 3
+regex.test('foo')  // false, lastIndex = 0
+```

.claude/skills/vercel-react-best-practices/rules/js-index-maps.md

@@ -0,0 +1,37 @@
+---
+title: Build Index Maps for Repeated Lookups
+impact: LOW-MEDIUM
+impactDescription: 1M ops to 2K ops
+tags: javascript, map, indexing, optimization, performance
+---
+
+## Build Index Maps for Repeated Lookups
+
+Multiple `.find()` calls by the same key should use a Map.
+
+**Incorrect (O(n) per lookup):**
+
+```typescript
+function processOrders(orders: Order[], users: User[]) {
+  return orders.map(order => ({
+    ...order,
+    user: users.find(u => u.id === order.userId)
+  }))
+}
+```
+
+**Correct (O(1) per lookup):**
+
+```typescript
+function processOrders(orders: Order[], users: User[]) {
+  const userById = new Map(users.map(u => [u.id, u]))
+
+  return orders.map(order => ({
+    ...order,
+    user: userById.get(order.userId)
+  }))
+}
+```
+
+Build map once (O(n)), then all lookups are O(1).
+For 1000 orders × 1000 users: 1M ops → 2K ops.

.claude/skills/vercel-react-best-practices/rules/js-length-check-first.md

@@ -0,0 +1,49 @@
+---
+title: Early Length Check for Array Comparisons
+impact: MEDIUM-HIGH
+impactDescription: avoids expensive operations when lengths differ
+tags: javascript, arrays, performance, optimization, comparison
+---
+
+## Early Length Check for Array Comparisons
+
+When comparing arrays with expensive operations (sorting, deep equality, serialization), check lengths first. If lengths differ, the arrays cannot be equal.
+
+In real-world applications, this optimization is especially valuable when the comparison runs in hot paths (event handlers, render loops).
+
+**Incorrect (always runs expensive comparison):**
+
+```typescript
+function hasChanges(current: string[], original: string[]) {
+  // Always sorts and joins, even when lengths differ
+  return current.sort().join() !== original.sort().join()
+}
+```
+
+Two O(n log n) sorts run even when `current.length` is 5 and `original.length` is 100. There is also overhead of joining the arrays and comparing the strings.
+
+**Correct (O(1) length check first):**
+
+```typescript
+function hasChanges(current: string[], original: string[]) {
+  // Early return if lengths differ
+  if (current.length !== original.length) {
+    return true
+  }
+  // Only sort/join when lengths match
+  const currentSorted = current.toSorted()
+  const originalSorted = original.toSorted()
+  for (let i = 0; i < currentSorted.length; i++) {
+    if (currentSorted[i] !== originalSorted[i]) {
+      return true
+    }
+  }
+  return false
+}
+```
+
+This new approach is more efficient because:
+- It avoids the overhead of sorting and joining the arrays when lengths differ
+- It avoids consuming memory for the joined strings (especially important for large arrays)
+- It avoids mutating the original arrays
+- It returns early when a difference is found

.claude/skills/vercel-react-best-practices/rules/js-min-max-loop.md

@@ -0,0 +1,82 @@
+---
+title: Use Loop for Min/Max Instead of Sort
+impact: LOW
+impactDescription: O(n) instead of O(n log n)
+tags: javascript, arrays, performance, sorting, algorithms
+---
+
+## Use Loop for Min/Max Instead of Sort
+
+Finding the smallest or largest element only requires a single pass through the array. Sorting is wasteful and slower.
+
+**Incorrect (O(n log n) - sort to find latest):**
+
+```typescript
+interface Project {
+  id: string
+  name: string
+  updatedAt: number
+}
+
+function getLatestProject(projects: Project[]) {
+  const sorted = [...projects].sort((a, b) => b.updatedAt - a.updatedAt)
+  return sorted[0]
+}
+```
+
+Sorts the entire array just to find the maximum value.
+
+**Incorrect (O(n log n) - sort for oldest and newest):**
+
+```typescript
+function getOldestAndNewest(projects: Project[]) {
+  const sorted = [...projects].sort((a, b) => a.updatedAt - b.updatedAt)
+  return { oldest: sorted[0], newest: sorted[sorted.length - 1] }
+}
+```
+
+Still sorts unnecessarily when only min/max are needed.
+
+**Correct (O(n) - single loop):**
+
+```typescript
+function getLatestProject(projects: Project[]) {
+  if (projects.length === 0) return null
+  
+  let latest = projects[0]
+  
+  for (let i = 1; i < projects.length; i++) {
+    if (projects[i].updatedAt > latest.updatedAt) {
+      latest = projects[i]
+    }
+  }
+  
+  return latest
+}
+
+function getOldestAndNewest(projects: Project[]) {
+  if (projects.length === 0) return { oldest: null, newest: null }
+  
+  let oldest = projects[0]
+  let newest = projects[0]
+  
+  for (let i = 1; i < projects.length; i++) {
+    if (projects[i].updatedAt < oldest.updatedAt) oldest = projects[i]
+    if (projects[i].updatedAt > newest.updatedAt) newest = projects[i]
+  }
+  
+  return { oldest, newest }
+}
+```
+
+Single pass through the array, no copying, no sorting.
+
+**Alternative (Math.min/Math.max for small arrays):**
+
+```typescript
+const numbers = [5, 2, 8, 1, 9]
+const min = Math.min(...numbers)
+const max = Math.max(...numbers)
+```
+
+This works for small arrays but can be slower for very large arrays due to spread operator limitations. Use the loop approach for reliability.

.claude/skills/vercel-react-best-practices/rules/js-set-map-lookups.md

@@ -0,0 +1,24 @@
+---
+title: Use Set/Map for O(1) Lookups
+impact: LOW-MEDIUM
+impactDescription: O(n) to O(1)
+tags: javascript, set, map, data-structures, performance
+---
+
+## Use Set/Map for O(1) Lookups
+
+Convert arrays to Set/Map for repeated membership checks.
+
+**Incorrect (O(n) per check):**
+
+```typescript
+const allowedIds = ['a', 'b', 'c', ...]
+items.filter(item => allowedIds.includes(item.id))
+```
+
+**Correct (O(1) per check):**
+
+```typescript
+const allowedIds = new Set(['a', 'b', 'c', ...])
+items.filter(item => allowedIds.has(item.id))
+```

.claude/skills/vercel-react-best-practices/rules/js-tosorted-immutable.md

@@ -0,0 +1,57 @@
+---
+title: Use toSorted() Instead of sort() for Immutability
+impact: MEDIUM-HIGH
+impactDescription: prevents mutation bugs in React state
+tags: javascript, arrays, immutability, react, state, mutation
+---
+
+## Use toSorted() Instead of sort() for Immutability
+
+`.sort()` mutates the array in place, which can cause bugs with React state and props. Use `.toSorted()` to create a new sorted array without mutation.
+
+**Incorrect (mutates original array):**
+
+```typescript
+function UserList({ users }: { users: User[] }) {
+  // Mutates the users prop array!
+  const sorted = useMemo(
+    () => users.sort((a, b) => a.name.localeCompare(b.name)),
+    [users]
+  )
+  return <div>{sorted.map(renderUser)}</div>
+}
+```
+
+**Correct (creates new array):**
+
+```typescript
+function UserList({ users }: { users: User[] }) {
+  // Creates new sorted array, original unchanged
+  const sorted = useMemo(
+    () => users.toSorted((a, b) => a.name.localeCompare(b.name)),
+    [users]
+  )
+  return <div>{sorted.map(renderUser)}</div>
+}
+```
+
+**Why this matters in React:**
+
+1. Props/state mutations break React's immutability model - React expects props and state to be treated as read-only
+2. Causes stale closure bugs - Mutating arrays inside closures (callbacks, effects) can lead to unexpected behavior
+
+**Browser support (fallback for older browsers):**
+
+`.toSorted()` is available in all modern browsers (Chrome 110+, Safari 16+, Firefox 115+, Node.js 20+). For older environments, use spread operator:
+
+```typescript
+// Fallback for older browsers
+const sorted = [...items].sort((a, b) => a.value - b.value)
+```
+
+**Other immutable array methods:**
+
+- `.toSorted()` - immutable sort
+- `.toReversed()` - immutable reverse
+- `.toSpliced()` - immutable splice
+- `.with()` - immutable element replacement

.claude/skills/vercel-react-best-practices/rules/rendering-activity.md

@@ -0,0 +1,26 @@
+---
+title: Use Activity Component for Show/Hide
+impact: MEDIUM
+impactDescription: preserves state/DOM
+tags: rendering, activity, visibility, state-preservation
+---
+
+## Use Activity Component for Show/Hide
+
+Use React's `<Activity>` to preserve state/DOM for expensive components that frequently toggle visibility.
+
+**Usage:**
+
+```tsx
+import { Activity } from 'react'
+
+function Dropdown({ isOpen }: Props) {
+  return (
+    <Activity mode={isOpen ? 'visible' : 'hidden'}>
+      <ExpensiveMenu />
+    </Activity>
+  )
+}
+```
+
+Avoids expensive re-renders and state loss.

.claude/skills/vercel-react-best-practices/rules/rendering-animate-svg-wrapper.md

@@ -0,0 +1,47 @@
+---
+title: Animate SVG Wrapper Instead of SVG Element
+impact: LOW
+impactDescription: enables hardware acceleration
+tags: rendering, svg, css, animation, performance
+---
+
+## Animate SVG Wrapper Instead of SVG Element
+
+Many browsers don't have hardware acceleration for CSS3 animations on SVG elements. Wrap SVG in a `<div>` and animate the wrapper instead.
+
+**Incorrect (animating SVG directly - no hardware acceleration):**
+
+```tsx
+function LoadingSpinner() {
+  return (
+    <svg 
+      className="animate-spin"
+      width="24" 
+      height="24" 
+      viewBox="0 0 24 24"
+    >
+      <circle cx="12" cy="12" r="10" stroke="currentColor" />
+    </svg>
+  )
+}
+```
+
+**Correct (animating wrapper div - hardware accelerated):**
+
+```tsx
+function LoadingSpinner() {
+  return (
+    <div className="animate-spin">
+      <svg 
+        width="24" 
+        height="24" 
+        viewBox="0 0 24 24"
+      >
+        <circle cx="12" cy="12" r="10" stroke="currentColor" />
+      </svg>
+    </div>
+  )
+}
+```
+
+This applies to all CSS transforms and transitions (`transform`, `opacity`, `translate`, `scale`, `rotate`). The wrapper div allows browsers to use GPU acceleration for smoother animations.

.claude/skills/vercel-react-best-practices/rules/rendering-conditional-render.md

@@ -0,0 +1,40 @@
+---
+title: Use Explicit Conditional Rendering
+impact: LOW
+impactDescription: prevents rendering 0 or NaN
+tags: rendering, conditional, jsx, falsy-values
+---
+
+## Use Explicit Conditional Rendering
+
+Use explicit ternary operators (`? :`) instead of `&&` for conditional rendering when the condition can be `0`, `NaN`, or other falsy values that render.
+
+**Incorrect (renders "0" when count is 0):**
+
+```tsx
+function Badge({ count }: { count: number }) {
+  return (
+    <div>
+      {count && <span className="badge">{count}</span>}
+    </div>
+  )
+}
+
+// When count = 0, renders: <div>0</div>
+// When count = 5, renders: <div><span class="badge">5</span></div>
+```
+
+**Correct (renders nothing when count is 0):**
+
+```tsx
+function Badge({ count }: { count: number }) {
+  return (
+    <div>
+      {count > 0 ? <span className="badge">{count}</span> : null}
+    </div>
+  )
+}
+
+// When count = 0, renders: <div></div>
+// When count = 5, renders: <div><span class="badge">5</span></div>
+```

.claude/skills/vercel-react-best-practices/rules/rendering-content-visibility.md

@@ -0,0 +1,38 @@
+---
+title: CSS content-visibility for Long Lists
+impact: HIGH
+impactDescription: faster initial render
+tags: rendering, css, content-visibility, long-lists
+---
+
+## CSS content-visibility for Long Lists
+
+Apply `content-visibility: auto` to defer off-screen rendering.
+
+**CSS:**
+
+```css
+.message-item {
+  content-visibility: auto;
+  contain-intrinsic-size: 0 80px;
+}
+```
+
+**Example:**
+
+```tsx
+function MessageList({ messages }: { messages: Message[] }) {
+  return (
+    <div className="overflow-y-auto h-screen">
+      {messages.map(msg => (
+        <div key={msg.id} className="message-item">
+          <Avatar user={msg.author} />
+          <div>{msg.content}</div>
+        </div>
+      ))}
+    </div>
+  )
+}
+```
+
+For 1000 messages, browser skips layout/paint for ~990 off-screen items (10× faster initial render).

.claude/skills/vercel-react-best-practices/rules/rendering-hoist-jsx.md

@@ -0,0 +1,46 @@
+---
+title: Hoist Static JSX Elements
+impact: LOW
+impactDescription: avoids re-creation
+tags: rendering, jsx, static, optimization
+---
+
+## Hoist Static JSX Elements
+
+Extract static JSX outside components to avoid re-creation.
+
+**Incorrect (recreates element every render):**
+
+```tsx
+function LoadingSkeleton() {
+  return <div className="animate-pulse h-20 bg-gray-200" />
+}
+
+function Container() {
+  return (
+    <div>
+      {loading && <LoadingSkeleton />}
+    </div>
+  )
+}
+```
+
+**Correct (reuses same element):**
+
+```tsx
+const loadingSkeleton = (
+  <div className="animate-pulse h-20 bg-gray-200" />
+)
+
+function Container() {
+  return (
+    <div>
+      {loading && loadingSkeleton}
+    </div>
+  )
+}
+```
+
+This is especially helpful for large and static SVG nodes, which can be expensive to recreate on every render.
+
+**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler automatically hoists static JSX elements and optimizes component re-renders, making manual hoisting unnecessary.

.claude/skills/vercel-react-best-practices/rules/rendering-hydration-no-flicker.md

@@ -0,0 +1,82 @@
+---
+title: Prevent Hydration Mismatch Without Flickering
+impact: MEDIUM
+impactDescription: avoids visual flicker and hydration errors
+tags: rendering, ssr, hydration, localStorage, flicker
+---
+
+## Prevent Hydration Mismatch Without Flickering
+
+When rendering content that depends on client-side storage (localStorage, cookies), avoid both SSR breakage and post-hydration flickering by injecting a synchronous script that updates the DOM before React hydrates.
+
+**Incorrect (breaks SSR):**
+
+```tsx
+function ThemeWrapper({ children }: { children: ReactNode }) {
+  // localStorage is not available on server - throws error
+  const theme = localStorage.getItem('theme') || 'light'
+  
+  return (
+    <div className={theme}>
+      {children}
+    </div>
+  )
+}
+```
+
+Server-side rendering will fail because `localStorage` is undefined.
+
+**Incorrect (visual flickering):**
+
+```tsx
+function ThemeWrapper({ children }: { children: ReactNode }) {
+  const [theme, setTheme] = useState('light')
+  
+  useEffect(() => {
+    // Runs after hydration - causes visible flash
+    const stored = localStorage.getItem('theme')
+    if (stored) {
+      setTheme(stored)
+    }
+  }, [])
+  
+  return (
+    <div className={theme}>
+      {children}
+    </div>
+  )
+}
+```
+
+Component first renders with default value (`light`), then updates after hydration, causing a visible flash of incorrect content.
+
+**Correct (no flicker, no hydration mismatch):**
+
+```tsx
+function ThemeWrapper({ children }: { children: ReactNode }) {
+  return (
+    <>
+      <div id="theme-wrapper">
+        {children}
+      </div>
+      <script
+        dangerouslySetInnerHTML={{
+          __html: `
+            (function() {
+              try {
+                var theme = localStorage.getItem('theme') || 'light';
+                var el = document.getElementById('theme-wrapper');
+                if (el) el.className = theme;
+              } catch (e) {}
+            })();
+          `,
+        }}
+      />
+    </>
+  )
+}
+```
+
+The inline script executes synchronously before showing the element, ensuring the DOM already has the correct value. No flickering, no hydration mismatch.
+
+This pattern is especially useful for theme toggles, user preferences, authentication states, and any client-only data that should render immediately without flashing default values.

.claude/skills/vercel-react-best-practices/rules/rendering-svg-precision.md

@@ -0,0 +1,28 @@
+---
+title: Optimize SVG Precision
+impact: LOW
+impactDescription: reduces file size
+tags: rendering, svg, optimization, svgo
+---
+
+## Optimize SVG Precision
+
+Reduce SVG coordinate precision to decrease file size. The optimal precision depends on the viewBox size, but in general reducing precision should be considered.
+
+**Incorrect (excessive precision):**
+
+```svg
+<path d="M 10.293847 20.847362 L 30.938472 40.192837" />
+```
+
+**Correct (1 decimal place):**
+
+```svg
+<path d="M 10.3 20.8 L 30.9 40.2" />
+```
+
+**Automate with SVGO:**
+
+```bash
+npx svgo --precision=1 --multipass icon.svg
+```

.claude/skills/vercel-react-best-practices/rules/rerender-defer-reads.md

@@ -0,0 +1,39 @@
+---
+title: Defer State Reads to Usage Point
+impact: MEDIUM
+impactDescription: avoids unnecessary subscriptions
+tags: rerender, searchParams, localStorage, optimization
+---
+
+## Defer State Reads to Usage Point
+
+Don't subscribe to dynamic state (searchParams, localStorage) if you only read it inside callbacks.
+
+**Incorrect (subscribes to all searchParams changes):**
+
+```tsx
+function ShareButton({ chatId }: { chatId: string }) {
+  const searchParams = useSearchParams()
+
+  const handleShare = () => {
+    const ref = searchParams.get('ref')
+    shareChat(chatId, { ref })
+  }
+
+  return <button onClick={handleShare}>Share</button>
+}
+```
+
+**Correct (reads on demand, no subscription):**
+
+```tsx
+function ShareButton({ chatId }: { chatId: string }) {
+  const handleShare = () => {
+    const params = new URLSearchParams(window.location.search)
+    const ref = params.get('ref')
+    shareChat(chatId, { ref })
+  }
+
+  return <button onClick={handleShare}>Share</button>
+}
+```

.claude/skills/vercel-react-best-practices/rules/rerender-dependencies.md

@@ -0,0 +1,45 @@
+---
+title: Narrow Effect Dependencies
+impact: LOW
+impactDescription: minimizes effect re-runs
+tags: rerender, useEffect, dependencies, optimization
+---
+
+## Narrow Effect Dependencies
+
+Specify primitive dependencies instead of objects to minimize effect re-runs.
+
+**Incorrect (re-runs on any user field change):**
+
+```tsx
+useEffect(() => {
+  console.log(user.id)
+}, [user])
+```
+
+**Correct (re-runs only when id changes):**
+
+```tsx
+useEffect(() => {
+  console.log(user.id)
+}, [user.id])
+```
+
+**For derived state, compute outside effect:**
+
+```tsx
+// Incorrect: runs on width=767, 766, 765...
+useEffect(() => {
+  if (width < 768) {
+    enableMobileMode()
+  }
+}, [width])
+
+// Correct: runs only on boolean transition
+const isMobile = width < 768
+useEffect(() => {
+  if (isMobile) {
+    enableMobileMode()
+  }
+}, [isMobile])
+```

.claude/skills/vercel-react-best-practices/rules/rerender-derived-state.md

@@ -0,0 +1,29 @@
+---
+title: Subscribe to Derived State
+impact: MEDIUM
+impactDescription: reduces re-render frequency
+tags: rerender, derived-state, media-query, optimization
+---
+
+## Subscribe to Derived State
+
+Subscribe to derived boolean state instead of continuous values to reduce re-render frequency.
+
+**Incorrect (re-renders on every pixel change):**
+
+```tsx
+function Sidebar() {
+  const width = useWindowWidth()  // updates continuously
+  const isMobile = width < 768
+  return <nav className={isMobile ? 'mobile' : 'desktop'}>
+}
+```
+
+**Correct (re-renders only when boolean changes):**
+
+```tsx
+function Sidebar() {
+  const isMobile = useMediaQuery('(max-width: 767px)')
+  return <nav className={isMobile ? 'mobile' : 'desktop'}>
+}
+```

.claude/skills/vercel-react-best-practices/rules/rerender-functional-setstate.md

@@ -0,0 +1,74 @@
+---
+title: Use Functional setState Updates
+impact: MEDIUM
+impactDescription: prevents stale closures and unnecessary callback recreations
+tags: react, hooks, useState, useCallback, callbacks, closures
+---
+
+## Use Functional setState Updates
+
+When updating state based on the current state value, use the functional update form of setState instead of directly referencing the state variable. This prevents stale closures, eliminates unnecessary dependencies, and creates stable callback references.
+
+**Incorrect (requires state as dependency):**
+
+```tsx
+function TodoList() {
+  const [items, setItems] = useState(initialItems)
+  
+  // Callback must depend on items, recreated on every items change
+  const addItems = useCallback((newItems: Item[]) => {
+    setItems([...items, ...newItems])
+  }, [items])  // ❌ items dependency causes recreations
+  
+  // Risk of stale closure if dependency is forgotten
+  const removeItem = useCallback((id: string) => {
+    setItems(items.filter(item => item.id !== id))
+  }, [])  // ❌ Missing items dependency - will use stale items!
+  
+  return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
+}
+```
+
+The first callback is recreated every time `items` changes, which can cause child components to re-render unnecessarily. The second callback has a stale closure bug—it will always reference the initial `items` value.
+
+**Correct (stable callbacks, no stale closures):**
+
+```tsx
+function TodoList() {
+  const [items, setItems] = useState(initialItems)
+  
+  // Stable callback, never recreated
+  const addItems = useCallback((newItems: Item[]) => {
+    setItems(curr => [...curr, ...newItems])
+  }, [])  // ✅ No dependencies needed
+  
+  // Always uses latest state, no stale closure risk
+  const removeItem = useCallback((id: string) => {
+    setItems(curr => curr.filter(item => item.id !== id))
+  }, [])  // ✅ Safe and stable
+  
+  return <ItemsEditor items={items} onAdd={addItems} onRemove={removeItem} />
+}
+```
+
+**Benefits:**
+
+1. **Stable callback references** - Callbacks don't need to be recreated when state changes
+2. **No stale closures** - Always operates on the latest state value
+3. **Fewer dependencies** - Simplifies dependency arrays and reduces memory leaks
+4. **Prevents bugs** - Eliminates the most common source of React closure bugs
+
+**When to use functional updates:**
+
+- Any setState that depends on the current state value
+- Inside useCallback/useMemo when state is needed
+- Event handlers that reference state
+- Async operations that update state
+
+**When direct updates are fine:**
+
+- Setting state to a static value: `setCount(0)`
+- Setting state from props/arguments only: `setName(newName)`
+- State doesn't depend on previous value
+
+**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, the compiler can automatically optimize some cases, but functional updates are still recommended for correctness and to prevent stale closure bugs.

.claude/skills/vercel-react-best-practices/rules/rerender-lazy-state-init.md

@@ -0,0 +1,58 @@
+---
+title: Use Lazy State Initialization
+impact: MEDIUM
+impactDescription: wasted computation on every render
+tags: react, hooks, useState, performance, initialization
+---
+
+## Use Lazy State Initialization
+
+Pass a function to `useState` for expensive initial values. Without the function form, the initializer runs on every render even though the value is only used once.
+
+**Incorrect (runs on every render):**
+
+```tsx
+function FilteredList({ items }: { items: Item[] }) {
+  // buildSearchIndex() runs on EVERY render, even after initialization
+  const [searchIndex, setSearchIndex] = useState(buildSearchIndex(items))
+  const [query, setQuery] = useState('')
+  
+  // When query changes, buildSearchIndex runs again unnecessarily
+  return <SearchResults index={searchIndex} query={query} />
+}
+
+function UserProfile() {
+  // JSON.parse runs on every render
+  const [settings, setSettings] = useState(
+    JSON.parse(localStorage.getItem('settings') || '{}')
+  )
+  
+  return <SettingsForm settings={settings} onChange={setSettings} />
+}
+```
+
+**Correct (runs only once):**
+
+```tsx
+function FilteredList({ items }: { items: Item[] }) {
+  // buildSearchIndex() runs ONLY on initial render
+  const [searchIndex, setSearchIndex] = useState(() => buildSearchIndex(items))
+  const [query, setQuery] = useState('')
+  
+  return <SearchResults index={searchIndex} query={query} />
+}
+
+function UserProfile() {
+  // JSON.parse runs only on initial render
+  const [settings, setSettings] = useState(() => {
+    const stored = localStorage.getItem('settings')
+    return stored ? JSON.parse(stored) : {}
+  })
+  
+  return <SettingsForm settings={settings} onChange={setSettings} />
+}
+```
+
+Use lazy initialization when computing initial values from localStorage/sessionStorage, building data structures (indexes, maps), reading from the DOM, or performing heavy transformations.
+
+For simple primitives (`useState(0)`), direct references (`useState(props.value)`), or cheap literals (`useState({})`), the function form is unnecessary.

.claude/skills/vercel-react-best-practices/rules/rerender-memo.md

@@ -0,0 +1,44 @@
+---
+title: Extract to Memoized Components
+impact: MEDIUM
+impactDescription: enables early returns
+tags: rerender, memo, useMemo, optimization
+---
+
+## Extract to Memoized Components
+
+Extract expensive work into memoized components to enable early returns before computation.
+
+**Incorrect (computes avatar even when loading):**
+
+```tsx
+function Profile({ user, loading }: Props) {
+  const avatar = useMemo(() => {
+    const id = computeAvatarId(user)
+    return <Avatar id={id} />
+  }, [user])
+
+  if (loading) return <Skeleton />
+  return <div>{avatar}</div>
+}
+```
+
+**Correct (skips computation when loading):**
+
+```tsx
+const UserAvatar = memo(function UserAvatar({ user }: { user: User }) {
+  const id = useMemo(() => computeAvatarId(user), [user])
+  return <Avatar id={id} />
+})
+
+function Profile({ user, loading }: Props) {
+  if (loading) return <Skeleton />
+  return (
+    <div>
+      <UserAvatar user={user} />
+    </div>
+  )
+}
+```
+
+**Note:** If your project has [React Compiler](https://react.dev/learn/react-compiler) enabled, manual memoization with `memo()` and `useMemo()` is not necessary. The compiler automatically optimizes re-renders.

.claude/skills/vercel-react-best-practices/rules/rerender-transitions.md

@@ -0,0 +1,40 @@
+---
+title: Use Transitions for Non-Urgent Updates
+impact: MEDIUM
+impactDescription: maintains UI responsiveness
+tags: rerender, transitions, startTransition, performance
+---
+
+## Use Transitions for Non-Urgent Updates
+
+Mark frequent, non-urgent state updates as transitions to maintain UI responsiveness.
+
+**Incorrect (blocks UI on every scroll):**
+
+```tsx
+function ScrollTracker() {
+  const [scrollY, setScrollY] = useState(0)
+  useEffect(() => {
+    const handler = () => setScrollY(window.scrollY)
+    window.addEventListener('scroll', handler, { passive: true })
+    return () => window.removeEventListener('scroll', handler)
+  }, [])
+}
+```
+
+**Correct (non-blocking updates):**
+
+```tsx
+import { startTransition } from 'react'
+
+function ScrollTracker() {
+  const [scrollY, setScrollY] = useState(0)
+  useEffect(() => {
+    const handler = () => {
+      startTransition(() => setScrollY(window.scrollY))
+    }
+    window.addEventListener('scroll', handler, { passive: true })
+    return () => window.removeEventListener('scroll', handler)
+  }, [])
+}
+```

.claude/skills/vercel-react-best-practices/rules/server-after-nonblocking.md

@@ -0,0 +1,73 @@
+---
+title: Use after() for Non-Blocking Operations
+impact: MEDIUM
+impactDescription: faster response times
+tags: server, async, logging, analytics, side-effects
+---
+
+## Use after() for Non-Blocking Operations
+
+Use Next.js's `after()` to schedule work that should execute after a response is sent. This prevents logging, analytics, and other side effects from blocking the response.
+
+**Incorrect (blocks response):**
+
+```tsx
+import { logUserAction } from '@/app/utils'
+
+export async function POST(request: Request) {
+  // Perform mutation
+  await updateDatabase(request)
+  
+  // Logging blocks the response
+  const userAgent = request.headers.get('user-agent') || 'unknown'
+  await logUserAction({ userAgent })
+  
+  return new Response(JSON.stringify({ status: 'success' }), {
+    status: 200,
+    headers: { 'Content-Type': 'application/json' }
+  })
+}
+```
+
+**Correct (non-blocking):**
+
+```tsx
+import { after } from 'next/server'
+import { headers, cookies } from 'next/headers'
+import { logUserAction } from '@/app/utils'
+
+export async function POST(request: Request) {
+  // Perform mutation
+  await updateDatabase(request)
+  
+  // Log after response is sent
+  after(async () => {
+    const userAgent = (await headers()).get('user-agent') || 'unknown'
+    const sessionCookie = (await cookies()).get('session-id')?.value || 'anonymous'
+    
+    logUserAction({ sessionCookie, userAgent })
+  })
+  
+  return new Response(JSON.stringify({ status: 'success' }), {
+    status: 200,
+    headers: { 'Content-Type': 'application/json' }
+  })
+}
+```
+
+The response is sent immediately while logging happens in the background.
+
+**Common use cases:**
+
+- Analytics tracking
+- Audit logging
+- Sending notifications
+- Cache invalidation
+- Cleanup tasks
+
+**Important notes:**
+
+- `after()` runs even if the response fails or redirects
+- Works in Server Actions, Route Handlers, and Server Components
+
+Reference: [https://nextjs.org/docs/app/api-reference/functions/after](https://nextjs.org/docs/app/api-reference/functions/after)

.claude/skills/vercel-react-best-practices/rules/server-cache-lru.md

@@ -0,0 +1,41 @@
+---
+title: Cross-Request LRU Caching
+impact: HIGH
+impactDescription: caches across requests
+tags: server, cache, lru, cross-request
+---
+
+## Cross-Request LRU Caching
+
+`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
+
+**Implementation:**
+
+```typescript
+import { LRUCache } from 'lru-cache'
+
+const cache = new LRUCache<string, any>({
+  max: 1000,
+  ttl: 5 * 60 * 1000  // 5 minutes
+})
+
+export async function getUser(id: string) {
+  const cached = cache.get(id)
+  if (cached) return cached
+
+  const user = await db.user.findUnique({ where: { id } })
+  cache.set(id, user)
+  return user
+}
+
+// Request 1: DB query, result cached
+// Request 2: cache hit, no DB query
+```
+
+Use when sequential user actions hit multiple endpoints needing the same data within seconds.
+
+**With Vercel's [Fluid Compute](https://vercel.com/docs/fluid-compute):** LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
+
+**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
+
+Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)

.claude/skills/vercel-react-best-practices/rules/server-cache-react.md

@@ -0,0 +1,26 @@
+---
+title: Per-Request Deduplication with React.cache()
+impact: MEDIUM
+impactDescription: deduplicates within request
+tags: server, cache, react-cache, deduplication
+---
+
+## Per-Request Deduplication with React.cache()
+
+Use `React.cache()` for server-side request deduplication. Authentication and database queries benefit most.
+
+**Usage:**
+
+```typescript
+import { cache } from 'react'
+
+export const getCurrentUser = cache(async () => {
+  const session = await auth()
+  if (!session?.user?.id) return null
+  return await db.user.findUnique({
+    where: { id: session.user.id }
+  })
+})
+```
+
+Within a single request, multiple calls to `getCurrentUser()` execute the query only once.

.claude/skills/vercel-react-best-practices/rules/server-parallel-fetching.md

@@ -0,0 +1,79 @@
+---
+title: Parallel Data Fetching with Component Composition
+impact: CRITICAL
+impactDescription: eliminates server-side waterfalls
+tags: server, rsc, parallel-fetching, composition
+---
+
+## Parallel Data Fetching with Component Composition
+
+React Server Components execute sequentially within a tree. Restructure with composition to parallelize data fetching.
+
+**Incorrect (Sidebar waits for Page's fetch to complete):**
+
+```tsx
+export default async function Page() {
+  const header = await fetchHeader()
+  return (
+    <div>
+      <div>{header}</div>
+      <Sidebar />
+    </div>
+  )
+}
+
+async function Sidebar() {
+  const items = await fetchSidebarItems()
+  return <nav>{items.map(renderItem)}</nav>
+}
+```
+
+**Correct (both fetch simultaneously):**
+
+```tsx
+async function Header() {
+  const data = await fetchHeader()
+  return <div>{data}</div>
+}
+
+async function Sidebar() {
+  const items = await fetchSidebarItems()
+  return <nav>{items.map(renderItem)}</nav>
+}
+
+export default function Page() {
+  return (
+    <div>
+      <Header />
+      <Sidebar />
+    </div>
+  )
+}
+```
+
+**Alternative with children prop:**
+
+```tsx
+async function Layout({ children }: { children: ReactNode }) {
+  const header = await fetchHeader()
+  return (
+    <div>
+      <div>{header}</div>
+      {children}
+    </div>
+  )
+}
+
+async function Sidebar() {
+  const items = await fetchSidebarItems()
+  return <nav>{items.map(renderItem)}</nav>
+}
+
+export default function Page() {
+  return (
+    <Layout>
+      <Sidebar />
+    </Layout>
+  )
+}
+```

.claude/skills/vercel-react-best-practices/rules/server-serialization.md

@@ -0,0 +1,38 @@
+---
+title: Minimize Serialization at RSC Boundaries
+impact: HIGH
+impactDescription: reduces data transfer size
+tags: server, rsc, serialization, props
+---
+
+## Minimize Serialization at RSC Boundaries
+
+The React Server/Client boundary serializes all object properties into strings and embeds them in the HTML response and subsequent RSC requests. This serialized data directly impacts page weight and load time, so **size matters a lot**. Only pass fields that the client actually uses.
+
+**Incorrect (serializes all 50 fields):**
+
+```tsx
+async function Page() {
+  const user = await fetchUser()  // 50 fields
+  return <Profile user={user} />
+}
+
+'use client'
+function Profile({ user }: { user: User }) {
+  return <div>{user.name}</div>  // uses 1 field
+}
+```
+
+**Correct (serializes only 1 field):**
+
+```tsx
+async function Page() {
+  const user = await fetchUser()
+  return <Profile name={user.name} />
+}
+
+'use client'
+function Profile({ name }: { name: string }) {
+  return <div>{name}</div>
+}
+```

.dockerignore

@@ -1,6 +1,9 @@
 # Ignore everything by default, selectively add things to context
 *
 
+# Documentation (for embeddings/search)
+!docs/
+
 # Platform - Libs
 !autogpt_platform/autogpt_libs/autogpt_libs/
 !autogpt_platform/autogpt_libs/pyproject.toml
@@ -16,6 +19,7 @@
 !autogpt_platform/backend/poetry.lock
 !autogpt_platform/backend/README.md
 !autogpt_platform/backend/.env
+!autogpt_platform/backend/gen_prisma_types_stub.py
 
 # Platform - Market
 !autogpt_platform/market/market/

.github/workflows/claude-dependabot.yml

@@ -74,13 +74,13 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable

.github/workflows/claude.yml

@@ -44,6 +44,12 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@v1.3.1
+        with:
+          large-packages: false  # slow
+          docker-images: false  # limited benefit
+
       # Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
       - name: Set up Python
         uses: actions/setup-python@v5
@@ -84,13 +90,13 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable

.github/workflows/copilot-setup-steps.yml

@@ -72,13 +72,13 @@ jobs:
 
       - name: Generate Prisma Client
         working-directory: autogpt_platform/backend
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: "21"
+          node-version: "22"
 
       - name: Enable corepack
         run: corepack enable
@@ -108,6 +108,16 @@ jobs:
       #   run: pnpm playwright install --with-deps chromium
 
       # Docker setup for development environment
+      - name: Free up disk space
+        run: |
+          # Remove large unused tools to free disk space for Docker builds
+          sudo rm -rf /usr/share/dotnet
+          sudo rm -rf /usr/local/lib/android
+          sudo rm -rf /opt/ghc
+          sudo rm -rf /opt/hostedtoolcache/CodeQL
+          sudo docker system prune -af
+          df -h
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
 
@@ -299,4 +309,4 @@ jobs:
           echo "✅ AutoGPT Platform development environment setup complete!"
           echo "🚀 Ready for development with Docker services running"
           echo "📝 Backend server: poetry run serve (port 8000)"
-          echo "🌐 Frontend server: pnpm dev (port 3000)"
+          echo "🌐 Frontend server: pnpm dev (port 3000)"

.github/workflows/platform-backend-ci.yml

@@ -134,7 +134,7 @@ jobs:
         run: poetry install
 
       - name: Generate Prisma Client
-        run: poetry run prisma generate
+        run: poetry run prisma generate && poetry run gen-prisma-stub
 
       - id: supabase
         name: Start Supabase
@@ -176,7 +176,7 @@ jobs:
           }
 
       - name: Run Database Migrations
-        run: poetry run prisma migrate dev --name updates
+        run: poetry run prisma migrate deploy
         env:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
           DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}

.github/workflows/platform-frontend-ci.yml

@@ -11,6 +11,11 @@ on:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
   merge_group:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || format('{0}-{1}', github.ref, github.event.pull_request.number || github.sha) }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
 
 defaults:
   run:
@@ -147,6 +152,14 @@ jobs:
         run: |
           cp ../.env.default ../.env
 
+      - name: Copy backend .env and set OpenAI API key
+        run: |
+          cp ../backend/.env.default ../backend/.env
+          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
+        env:
+          # Used by E2E test data script to generate embeddings for approved store agents
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
 
@@ -222,13 +235,25 @@ jobs:
 
       - name: Run Playwright tests
         run: pnpm test:no-build
+        continue-on-error: false
 
-      - name: Upload Playwright artifacts
-        if: failure()
+      - name: Upload Playwright report
+        if: always()
         uses: actions/upload-artifact@v4
         with:
           name: playwright-report
           path: playwright-report
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Upload Playwright test results
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-test-results
+          path: test-results
+          if-no-files-found: ignore
+          retention-days: 3
 
       - name: Print Final Docker Compose logs
         if: always()

.github/workflows/platform-fullstack-ci.yml

@@ -12,6 +12,10 @@ on:
       - "autogpt_platform/**"
   merge_group:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
+
 defaults:
   run:
     shell: bash

.github/workflows/repo-close-stale-issues.yml

@@ -11,7 +11,7 @@ jobs:
   stale:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@v9
+      - uses: actions/stale@v10
         with:
           # operations-per-run: 5000
           stale-issue-message: >

.github/workflows/repo-pr-label.yml

@@ -61,6 +61,6 @@ jobs:
       pull-requests: write
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/labeler@v5
+      - uses: actions/labeler@v6
         with:
           sync-labels: true

autogpt_platform/Makefile

@@ -1,4 +1,4 @@
-.PHONY: start-core stop-core logs-core format lint migrate run-backend run-frontend
+.PHONY: start-core stop-core logs-core format lint migrate run-backend run-frontend load-store-agents
 
 # Run just Supabase + Redis + RabbitMQ
 start-core:
@@ -6,12 +6,14 @@ start-core:
 
 # Stop core services
 stop-core:
-	docker compose stop deps
+	docker compose stop 
 
 reset-db:
+	docker compose stop db
 	rm -rf db/docker/volumes/db/data
 	cd backend && poetry run prisma migrate deploy
 	cd backend && poetry run prisma generate
+	cd backend && poetry run gen-prisma-stub
 	
 # View logs for core services
 logs-core:
@@ -33,6 +35,7 @@ init-env:
 migrate:
 	cd backend && poetry run prisma migrate deploy
 	cd backend && poetry run prisma generate
+	cd backend && poetry run gen-prisma-stub
 
 run-backend:
 	cd backend && poetry run app
@@ -42,7 +45,10 @@ run-frontend:
 
 test-data:
 	cd backend && poetry run python test/test_data_creator.py
-	
+
+load-store-agents:
+	cd backend && poetry run load-store-agents
+
 help:
 	@echo "Usage: make <target>"
 	@echo "Targets:"
@@ -54,4 +60,5 @@ help:
 	@echo "  migrate - Run backend database migrations"
 	@echo "  run-backend - Run the backend FastAPI server"
 	@echo "  run-frontend - Run the frontend Next.js development server"
-	@echo "  test-data - Run the test data creator"
+	@echo "  test-data - Run the test data creator"
+	@echo "  load-store-agents - Load store agents from agents/ folder into test database"

autogpt_platform/autogpt_libs/autogpt_libs/api_key/keysmith.py

@@ -57,6 +57,9 @@ class APIKeySmith:
 
     def hash_key(self, raw_key: str) -> tuple[str, str]:
         """Migrate a legacy hash to secure hash format."""
+        if not raw_key.startswith(self.PREFIX):
+            raise ValueError("Key without 'agpt_' prefix would fail validation")
+
         salt = self._generate_salt()
         hash = self._hash_key_with_salt(raw_key, salt)
         return hash, salt.hex()

autogpt_platform/autogpt_libs/autogpt_libs/auth/helpers.py

@@ -1,29 +1,25 @@
 from fastapi import FastAPI
-from fastapi.openapi.utils import get_openapi
 
 from .jwt_utils import bearer_jwt_auth
 
 
 def add_auth_responses_to_openapi(app: FastAPI) -> None:
     """
-    Set up custom OpenAPI schema generation that adds 401 responses
+    Patch a FastAPI instance's `openapi()` method to add 401 responses
     to all authenticated endpoints.
 
     This is needed when using HTTPBearer with auto_error=False to get proper
     401 responses instead of 403, but FastAPI only automatically adds security
     responses when auto_error=True.
     """
+    # Wrap current method to allow stacking OpenAPI schema modifiers like this
+    wrapped_openapi = app.openapi
 
     def custom_openapi():
         if app.openapi_schema:
             return app.openapi_schema
 
-        openapi_schema = get_openapi(
-            title=app.title,
-            version=app.version,
-            description=app.description,
-            routes=app.routes,
-        )
+        openapi_schema = wrapped_openapi()
 
         # Add 401 response to all endpoints that have security requirements
         for path, methods in openapi_schema["paths"].items():

autogpt_platform/backend/.env.default

@@ -58,6 +58,13 @@ V0_API_KEY=
 OPEN_ROUTER_API_KEY=
 NVIDIA_API_KEY=
 
+# Langfuse Prompt Management
+# Used for managing the CoPilot system prompt externally
+# Get credentials from https://cloud.langfuse.com or your self-hosted instance
+LANGFUSE_PUBLIC_KEY=
+LANGFUSE_SECRET_KEY=
+LANGFUSE_HOST=https://cloud.langfuse.com
+
 # OAuth Credentials
 # For the OAuth callback URL, use <your_frontend_url>/auth/integrations/oauth_callback,
 # e.g. http://localhost:3000/auth/integrations/oauth_callback
@@ -134,13 +141,6 @@ POSTMARK_WEBHOOK_TOKEN=
 # Error Tracking
 SENTRY_DSN=
 
-# Cloudflare Turnstile (CAPTCHA) Configuration
-# Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
-# This is the backend secret key
-TURNSTILE_SECRET_KEY=
-# This is the verify URL
-TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
-
 # Feature Flags
 LAUNCH_DARKLY_SDK_KEY=
 

autogpt_platform/backend/.gitignore

@@ -18,3 +18,4 @@ load-tests/results/
 load-tests/*.json
 load-tests/*.log
 load-tests/node_modules/*
+migrations/*/rollback*.sql

autogpt_platform/backend/Dockerfile

@@ -48,7 +48,8 @@ RUN poetry install --no-ansi --no-root
 # Generate Prisma client
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-RUN poetry run prisma generate
+COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
+RUN poetry run prisma generate && poetry run gen-prisma-stub
 
 FROM debian:13-slim AS server_dependencies
 
@@ -99,6 +100,7 @@ COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migration
 FROM server_dependencies AS server
 
 COPY autogpt_platform/backend /app/autogpt_platform/backend
+COPY docs /app/docs
 RUN poetry install --no-ansi --only-root
 
 ENV PORT=8000

autogpt_platform/backend/TESTING.md

@@ -108,7 +108,7 @@ import fastapi.testclient
 import pytest
 from pytest_snapshot.plugin import Snapshot
 
-from backend.server.v2.myroute import router
+from backend.api.features.myroute import router
 
 app = fastapi.FastAPI()
 app.include_router(router)
@@ -149,7 +149,7 @@ These provide the easiest way to set up authentication mocking in test modules:
 import fastapi
 import fastapi.testclient
 import pytest
-from backend.server.v2.myroute import router
+from backend.api.features.myroute import router
 
 app = fastapi.FastAPI()
 app.include_router(router)

autogpt_platform/backend/agents/StoreAgent_rows.csv

@@ -0,0 +1,242 @@
+listing_id,storeListingVersionId,slug,agent_name,agent_video,agent_image,featured,sub_heading,description,categories,useForOnboarding,is_available
+6e60a900-9d7d-490e-9af2-a194827ed632,d85882b8-633f-44ce-a315-c20a8c123d19,flux-ai-image-generator,Flux AI Image Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/ca154dd1-140e-454c-91bd-2d8a00de3f08.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/577d995d-bc38-40a9-a23f-1f30f5774bdb.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/415db1b7-115c-43ab-bd6c-4e9f7ef95be1.jpg""]",false,Transform ideas into breathtaking images,"Transform ideas into breathtaking images with this AI-powered Image Generator. Using cutting-edge Flux AI technology, the tool crafts highly detailed, photorealistic visuals from simple text prompts. Perfect for artists, marketers, and content creators, this generator produces unique images tailored to user specifications. From fantastical scenes to lifelike portraits, users can unleash creativity with professional-quality results in seconds. Easy to use and endlessly versatile, bring imagination to life with the AI Image Generator today!","[""creative""]",false,true
+f11fc6e9-6166-4676-ac5d-f07127b270c1,c775f60d-b99f-418b-8fe0-53172258c3ce,youtube-transcription-scraper,YouTube Transcription Scraper,https://youtu.be/H8S3pU68lGE,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/65bce54b-0124-4b0d-9e3e-f9b89d0dc99e.jpg""]",false,Fetch the transcriptions from the most popular YouTube videos in your chosen topic,"Effortlessly gather transcriptions from multiple YouTube videos with this agent. It scrapes and compiles video transcripts into a clean, organized list, making it easy to extract insights, quotes, or content from various sources in one go. Ideal for researchers, content creators, and marketers looking to quickly analyze or repurpose video content.","[""writing""]",false,true
+17908889-b599-4010-8e4f-bed19b8f3446,6e16e65a-ad34-4108-b4fd-4a23fced5ea2,business-ownerceo-finder,Decision Maker Lead Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/1020d94e-b6a2-4fa7-bbdf-2c218b0de563.jpg""]",false,Contact CEOs today,"Find the key decision-makers you need, fast.
+
+This agent identifies business owners or CEOs of local companies in any area you choose. Simply enter what kind of businesses you’re looking for and where, and it will:
+
+* Search the area and gather public information
+* Return names, roles, and contact details when available
+* Provide smart Google search suggestions if details aren’t found
+
+Perfect for:
+
+* B2B sales teams seeking verified leads
+* Recruiters sourcing local talent
+* Researchers looking to connect with business leaders
+
+Save hours of manual searching and get straight to the people who matter most.","[""business""]",true,true
+72beca1d-45ea-4403-a7ce-e2af168ee428,415b7352-0dc6-4214-9d87-0ad3751b711d,smart-meeting-brief,Smart Meeting Prep,https://youtu.be/9ydZR2hkxaY,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2f116ce1-63ae-4d39-a5cd-f514defc2b97.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/0a71a60a-2263-4f12-9836-9c76ab49f155.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/95327695-9184-403c-907a-a9d3bdafa6a5.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2bc77788-790b-47d4-8a61-ce97b695e9f5.png""]",true,Business meeting briefings delivered daily,"Never walk into a meeting unprepared again. Every day at 4 pm, the Smart Meeting Prep Agent scans your calendar for tomorrow's external meetings. It reviews your past email exchanges, researches each participant's background and role, and compiles the insights into a concise briefing, so you can close your workday ready for tomorrow's calls.
+
+How It Works
+1. At 4 pm, the agent scans your calendar and identifies external meetings scheduled for the next day.
+2. It reviews recent email threads with each participant to surface key relationship history and communication context.
+3. It conducts online research to gather publicly available information on roles, company backgrounds, and relevant professional data.
+4. It produces a unified briefing for each participant, including past exchange highlights, profile notes, and strategic conversation points.","[""personal""]",true,true
+9fa5697a-617b-4fae-aea0-7dbbed279976,b8ceb480-a7a2-4c90-8513-181a49f7071f,automated-support-ai,Automated Support Agent,https://youtu.be/nBMfu_5sgDA,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/ed56febc-2205-4179-9e7e-505d8500b66c.png""]",true,Automate up to 80 percent of inbound support emails,"Overview:
+Support teams spend countless hours on basic tickets. This agent automates repetitive customer support tasks. It reads incoming requests, researches your knowledge base, and responds automatically when confident. When unsure, it escalates to a human for final resolution.
+
+How it Works:
+New support emails are routed to the agent.
+The agent checks internal documentation for answers.
+It measures confidence in the answer found and either replies directly or escalates to a human.
+
+Business Value:
+Automating the easy 80 percent of support tickets allows your team to focus on high-value, complex customer issues, improving efficiency and response times.","[""business""]",false,true
+2bdac92b-a12c-4131-bb46-0e3b89f61413,31daf49d-31d3-476b-aa4c-099abc59b458,unspirational-poster-maker,Unspirational Poster Maker,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/6a490dac-27e5-405f-a4c4-8d1c55b85060.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/d343fbb5-478c-4e38-94df-4337293b61f1.jpg""]",false,Because adulting is hard,"This witty AI agent generates hilariously relatable ""motivational"" posters that tackle the everyday struggles of procrastination, overthinking, and workplace chaos with a blend of absurdity and sarcasm. From goldfish facing impossible tasks to cats in existential crises, The Unspirational Poster Maker designs tongue-in-cheek graphics and captions that mock productivity clichés and embrace our collective struggles to ""get it together."" Perfect for adding a touch of humour to the workday, these posters remind us that sometimes, all we can do is laugh at the chaos.","[""creative""]",false,true
+9adf005e-2854-4cc7-98cf-f7103b92a7b7,a03b0d8c-4751-43d6-a54e-c3b7856ba4e3,ai-shortform-video-generator-create-viral-ready-content,AI Video Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/8d2670b9-fea5-4966-a597-0a4511bffdc3.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/aabe8aec-0110-4ce7-a259-4f86fe8fe07d.png""]",false,Create Viral-Ready Shorts Content in Seconds,"OVERVIEW
+Transform any trending headline or broad topic into a polished, vertical short-form video in a single run.  
+The agent automates research, scriptwriting, metadata creation, and Revid.ai rendering, returning one ready-to-publish MP4 plus its title, script and hashtags.
+
+HOW IT WORKS
+1. Input a topic or an exact news headline.  
+2. The agent fetches live search results and selects the most engaging related story.  
+3. Key facts are summarised into concise research notes.  
+4. Claude writes a 30–35 second script with visual cues, a three-second hook, tension loops, and a call-to-action.  
+5. GPT-4o generates an eye-catching title and one or two discoverability hashtags.  
+6. The script is sent to a state-of-the-art AI video generator to render a single 9:16 MP4 (default: 720 p, 30 fps, voice “Brian”, style “movingImage”, music “Bladerunner 2049”).  
+   – All voice, style and resolution settings can be adjusted in the Builder before you press ""Run"".  
+7. Output delivered: Title, Script, Hashtags, Video URL.
+
+KEY USE CASES
+- Broad-topic explainers (e.g. “Artificial Intelligence” or “Climate Tech”).  
+- Real-time newsjacking with a specific breaking headline.  
+- Product-launch spotlights and quick event recaps while interest is high.  
+
+BUSINESS VALUE
+- One-click speed: from idea to finished video in minutes.  
+- Consistent brand look: Revid presets keep voice, style and aspect ratio on spec.  
+- No-code workflow: marketers create social video without design or development queues.  
+- Cloud convenience: Auto-GPT Cloud users are pre-configured with all required keys.  
+  Self-hosted users simply add OpenAI, Anthropic, Perplexity (OpenRouter/Jina) and Revid keys once.
+
+IMPORTANT NOTES
+- The agent outputs exactly one video per execution. Run it again for additional shorts.  
+- Video rendering time varies; AI-generated footage may take several minutes.","[""writing""]",false,true
+864e48ef-fee5-42c1-b6a4-2ae139db9fc1,55d40473-0f31-4ada-9e40-d3a7139fcbd4,automated-blog-writer,Automated SEO Blog Writer,https://youtu.be/nKcDCbDVobs,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/2dd5f95b-5b30-4bf8-a11b-bac776c5141a.jpg""]",true,"Automate research, writing, and publishing for high-ranking blog posts","Scale your blog with a fully automated content engine. The Automated SEO Blog Writer learns your brand voice, finds high-demand keywords, and creates SEO-optimized articles that attract organic traffic and boost visibility.
+
+How it works:
+
+1. Share your pitch, website, and values.
+2. The agent studies your site and uncovers proven SEO opportunities.
+3. It spends two hours researching and drafting each post.
+4. You set the cadence—publishing runs on autopilot.
+
+Business value: Consistently publish research-backed, optimized posts that build domain authority, rankings, and thought leadership while you focus on what matters most.
+
+Use cases:
+• Founders: Keep your blog active with no time drain.
+• Agencies: Deliver scalable SEO content for clients.
+• Strategists: Automate execution, focus on strategy.
+• Marketers: Drive steady organic growth.
+• Local businesses: Capture nearby search traffic.","[""writing""]",false,true
+6046f42e-eb84-406f-bae0-8e052064a4fa,a548e507-09a7-4b30-909c-f63fcda10fff,lead-finder-local-businesses,Lead Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/abd6605f-d5f8-426b-af36-052e8ba5044f.webp""]",false,Auto-Prospect Like a Pro,"Turbo-charge your local lead generation with the AutoGPT Marketplace’s top Google Maps prospecting agent. “Lead Finder: Local Businesses” delivers verified, ready-to-contact prospects in any niche and city—so you can focus on closing, not searching.
+
+**WHAT IT DOES**
+• Searches Google Maps via the official API (no scraping)
+• Prompts like “dentists in Chicago” or “coffee shops near me”
+• Returns: Name, Website, Rating, Reviews, **Phone & Address**
+• Exports instantly to your CRM, sheet, or outreach workflow
+
+**WHY YOU’LL LOVE IT**
+✓ Hyper-targeted leads in minutes
+✓ Unlimited searches & locations
+✓ Zero CAPTCHAs or IP blocks
+✓ Works on AutoGPT Cloud or self-hosted (with your API key)
+✓ Cut prospecting time by 90%
+
+**PERFECT FOR**
+— Marketers & PPC agencies
+— SEO consultants & designers
+— SaaS founders & sales teams
+
+Stop scrolling directories—start filling your pipeline. Start now and let AI prospect while you profit.
+
+→ Click *Add to Library* and own your market today.","[""business""]",true,true
+f623c862-24e9-44fc-8ce8-d8282bb51ad2,eafa21d3-bf14-4f63-a97f-a5ee41df83b3,linkedin-post-generator,LinkedIn Post Generator,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/297f6a8e-81a8-43e2-b106-c7ad4a5662df.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/fceebdc1-aef6-4000-97fc-4ef587f56bda.png""]",false,Auto‑craft LinkedIn gold,"Create research‑driven, high‑impact LinkedIn posts in minutes. This agent searches YouTube for the best videos on your chosen topic, pulls their transcripts, and distils the most valuable insights into a polished post ready for your company page or personal feed.  
+
+FEATURES  
+• Automated YouTube research – discovers and analyses top‑ranked videos so you don’t have to  
+• AI‑curated synthesis – combines multiple transcripts into one authoritative narrative  
+• Full creative control – adjust style, tone, objective, opinion, clarity, target word count and number of videos  
+• LinkedIn‑optimised output – hook, 2‑3 key points, CTA, strategic line breaks, 3‑5 hashtags, no markdown  
+• One‑click publish – returns a ready‑to‑post text block (≤1 300 characters)  
+
+HOW IT WORKS  
+1. Enter a topic and your preferred writing parameters.  
+2. The agent builds a YouTube search, fetches the page, and extracts the top N video URLs.  
+3. It pulls each transcript, then feeds them—plus your settings—into Claude 3.5 Sonnet.  
+4. The model writes a concise, engaging post designed for maximum LinkedIn engagement.  
+
+USE CASES  
+• Thought‑leadership updates backed by fresh video research  
+• Rapid industry summaries after major events, webinars, or conferences  
+• Consistent LinkedIn content for busy founders, marketers, and creators  
+
+WHY YOU’LL LOVE IT  
+Save hours of manual research, avoid surface‑level hot‑takes, and publish posts that showcase real expertise—without the heavy lift.","[""writing""]",true,true
+7d4120ad-b6b3-4419-8bdb-7dd7d350ef32,e7bb29a1-23c7-4fee-aa3b-5426174b8c52,youtube-to-linkedin-post-converter,YouTube to LinkedIn Post Converter,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/f084b326-a708-4396-be51-7ba59ad2ef32.png""]",false,Transform Your YouTube Videos into Engaging LinkedIn Posts with AI,"WHAT IT DOES: 
+This agent converts YouTube video content into a LinkedIn post by analyzing the video's transcript. It provides you with a tailored post that reflects the core ideas, key takeaways, and tone of the original video, optimizing it for engagement on LinkedIn.
+
+HOW IT WORKS:
+- You provide the URL to the YouTube video (required)
+- You can choose the structure for the LinkedIn post (e.g., Personal Achievement Story, Lesson Learned, Thought Leadership, etc.)
+- You can also select the tone (e.g., Inspirational, Analytical, Conversational, etc.)
+- The transcript of the video is analyzed by the GPT-4 model and the Claude 3.5 Sonnet model
+- The models extract key insights, memorable quotes, and the main points from the video
+- You’ll receive a LinkedIn post, formatted according to your chosen structure and tone, optimized for professional engagement
+
+INPUTS:
+- Source YouTube Video – Provide the URL to the YouTube video
+- Structure – Choose the post format (e.g., Personal Achievement Story, Thought Leadership, etc.)
+- Content – Specify the main message or idea of the post (e.g., Hot Take, Key Takeaways, etc.)
+- Tone – Select the tone for the post (e.g., Conversational, Inspirational, etc.)
+
+OUTPUT:
+- LinkedIn Post – A well-crafted, AI-generated LinkedIn post with a professional tone, based on the video content and your specified preferences
+
+Perfect for content creators, marketers, and professionals who want to repurpose YouTube videos for LinkedIn and boost their professional branding.","[""writing""]",false,true
+c61d6a83-ea48-4df8-b447-3da2d9fe5814,00fdd42c-a14c-4d19-a567-65374ea0e87f,personalized-morning-coffee-newsletter,Personal Newsletter,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/f4b38e4c-8166-4caf-9411-96c9c4c82d4c.png""]",false,Start your day with personalized AI newsletters that deliver credibility and context for every interest or mood.,"This Personal Newsletter Agent provides a bespoke daily digest on your favorite topics and tone. Whether you prefer industry insights, lighthearted reads, or breaking news, this agent crafts your own unique newsletter to keep you informed and entertained.
+
+
+How It Works
+1. Enter your favorite topics, industries, or areas of interest.
+2. Choose your tone—professional, casual, or humorous.
+3. Set your preferred delivery cadence: daily or weekly.
+4. The agent scans top sources and compiles 3–5 engaging stories, insights, and fun facts into a conversational newsletter.
+
+Skip the morning scroll and enjoy a thoughtfully curated newsletter designed just for you. Stay ahead of trends, spark creative ideas, and enjoy an effortless, informed start to your day.
+
+
+Use Cases
+• Executives: Get a daily digest of market updates and leadership insights.
+• Marketers: Receive curated creative trends and campaign inspiration.
+• Entrepreneurs: Stay updated on your industry without information overload.","[""research""]",true,true
+e2e49cfc-4a39-4d62-a6b3-c095f6d025ff,fc2c9976-0962-4625-a27b-d316573a9e7f,email-address-finder,Email Scout - Contact Finder Assistant,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/da8a690a-7a8b-4c1d-b6f8-e2f840c0205d.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/6a2ac25c-1609-4881-8140-e6da2421afb3.jpg"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/26179263-fe06-45bd-b6a0-0754660a0a46.jpg""]",false,Find contact details from name and location using AI search,"Finding someone's professional email address can be time-consuming and frustrating. Manual searching across multiple websites, social profiles, and business directories often leads to dead ends or outdated information.
+
+Email Scout automates this process by intelligently searching across publicly available sources when you provide a person's name and location. Simply input basic information like ""Tim Cook, USA"" or ""Sarah Smith, London"" and let the AI assistant do the work of finding potential contact details.
+
+Key Features:
+- Quick search from just name and location
+- Scans multiple public sources
+- Automated AI-powered search process
+- Easy to use with simple inputs
+
+Perfect for recruiters, business development professionals, researchers, and anyone needing to establish professional contact.
+
+Note: This tool searches only publicly available information. Search results depend on what contact information people have made public. Some searches may not yield results if the information isn't publicly accessible.","[""""]",false,true
+81bcc372-0922-4a36-bc35-f7b1e51d6939,e437cc95-e671-489d-b915-76561fba8c7f,ai-youtube-to-blog-converter,YouTube Video to SEO Blog Writer,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/239e5a41-2515-4e1c-96ef-31d0d37ecbeb.webp"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/c7d96966-786f-4be6-ad7d-3a51c84efc0e.png"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/0275a74c-e2c2-4e29-a6e4-3a616c3c35dd.png""]",false,One link. One click. One powerful blog post.,"Effortlessly transform your YouTube videos into high-quality, SEO-optimized blog posts.
+
+Your videos deserve a second life—in writing.  
+Make your content work twice as hard by repurposing it into engaging, searchable articles.
+
+Perfect for content creators, marketers, and bloggers, this tool analyzes video content and generates well-structured blog posts tailored to your tone, audience, and word count. Just paste a YouTube URL and let the AI handle the rest.
+
+FEATURES
+
+• CONTENT ANALYSIS  
+  Extracts key points from the video while preserving your message and intent.
+
+• CUSTOMIZABLE OUTPUT  
+  Select a tone that fits your audience: casual, professional, educational, or formal.
+
+• SEO OPTIMIZATION  
+  Automatically creates engaging titles and structured subheadings for better search visibility.
+
+• USER-FRIENDLY  
+  Repurpose your videos into written content to expand your reach and improve accessibility.
+
+Whether you're looking to grow your blog, boost SEO, or simply get more out of your content, the AI YouTube-to-Blog Converter makes it effortless.
+","[""writing""]",true,true
+5c3510d2-fc8b-4053-8e19-67f53c86eb1a,f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9,ai-webpage-copy-improver,AI Webpage Copy Improver,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/d562d26f-5891-4b09-8859-fbb205972313.jpg""]",false,Boost Your Website's Search Engine Performance,"Elevate your web content with this powerful AI Webpage Copy Improver. Designed for marketers, SEO specialists, and web developers, this tool analyses and enhances website copy for maximum impact. Using advanced language models, it optimizes text for better clarity, SEO performance, and increased conversion rates. The AI examines your existing content, identifies areas for improvement, and generates refined copy that maintains your brand voice while boosting engagement. From homepage headlines to product descriptions, transform your web presence with AI-driven insights. Improve readability, incorporate targeted keywords, and craft compelling calls-to-action - all with the click of a button. Take your digital marketing to the next level with the AI Webpage Copy Improver.","[""marketing""]",true,true
+94d03bd3-7d44-4d47-b60c-edb2f89508d6,b6f6f0d3-49f4-4e3b-8155-ffe9141b32c0,domain-name-finder,Domain Name Finder,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/28545e09-b2b8-4916-b4c6-67f982510a78.jpeg""]",false,Instantly generate brand-ready domain names that are actually available,"Overview:
+Finding a domain name that fits your brand shouldn’t take hours of searching and failed checks. The Domain Name Finder Agent turns your pitch into hundreds of creative, brand-ready domain ideas—filtered by live availability so every result is actionable.
+
+How It Works
+1. Input your product pitch, company name, or core keywords.
+2. The agent analyzes brand tone, audience, and industry context.
+3. It generates a list of unique, memorable domains that match your criteria.
+4. All names are pre-filtered for real-time availability, so you can register immediately.
+
+
+Business Value
+Save hours of guesswork and eliminate dead ends. Accelerate brand launches, startup naming, and campaign creation with ready-to-claim domains.
+
+
+Key Use Cases
+• Startup Founders: Quickly find brand-ready domains for MVP launches or rebrands.
+• Marketers: Test name options across campaigns with instant availability data.
+• Entrepreneurs: Validate ideas faster with instant domain options.","[""business""]",false,true
+7a831906-daab-426f-9d66-bcf98d869426,516d813b-d1bc-470f-add7-c63a4b2c2bad,ai-function,AI Function,,"[""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/620e8117-2ee1-4384-89e6-c2ef4ec3d9c9.webp"",""https://storage.googleapis.com/agpt-prod-website-artifacts/users/b3e41ea4-2f4c-4964-927c-fe682d857bad/images/476259e2-5a79-4a7b-8e70-deeebfca70d7.png""]",false,Never Code Again,"AI FUNCTION MAGIC  
+Your AI‑powered assistant for turning plain‑English descriptions into working Python functions.  
+
+HOW IT WORKS  
+1. Describe what the function should do.  
+2. Specify the inputs it needs.  
+3. Receive the generated Python code.  
+
+FEATURES  
+- Effortless Function Generation: convert natural‑language specs into complete functions.  
+- Customizable Inputs: define the parameters that matter to you.  
+- Versatile Use Cases: simulate data, automate tasks, prototype ideas.  
+- Seamless Integration: add the generated function directly to your codebase.  
+
+EXAMPLE  
+Request: “Create a function that generates 20 examples of fake people, each with a name, date of birth, job title, and age.”  
+Input parameter: number_of_people (default 20)  
+Result: a list of dictionaries such as  
+[  
+  { ""name"": ""Emma Martinez"",  ""date_of_birth"": ""1992‑11‑03"", ""job_title"": ""Data Analyst"",        ""age"": 32 },  
+  { ""name"": ""Liam O’Connor"",  ""date_of_birth"": ""1985‑07‑19"", ""job_title"": ""Marketing Manager"",  ""age"": 39 },  
+  …18 more entries…  
+]","[""development""]",false,true

autogpt_platform/backend/agents/agent_31daf49d-31d3-476b-aa4c-099abc59b458.json

@@ -0,0 +1,590 @@
+{
+  "id": "7b2e2095-782a-4f8d-adda-e62b661bccf5",
+  "version": 29,
+  "is_active": false,
+  "name": "Unspirational Poster Maker",
+  "description": "This witty AI agent generates hilariously relatable \"motivational\" posters that tackle the everyday struggles of procrastination, overthinking, and workplace chaos with a blend of absurdity and sarcasm. From goldfish facing impossible tasks to cats in existential crises, The Unspirational Poster Maker designs tongue-in-cheek graphics and captions that mock productivity clich\u00e9s and embrace our collective struggles to \"get it together.\" Perfect for adding a touch of humour to the workday, these posters remind us that sometimes, all we can do is laugh at the chaos.",
+  "instructions": null,
+  "recommended_schedule_cron": null,
+  "nodes": [
+    {
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+      "input_default": {
+        "name": "Generated Image",
+        "description": "The resulting generated image ready for you to review and post."
+      },
+      "metadata": {
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+          "y": 80.49068076698347
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+      "input_links": [
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+          "id": "c6c511e8-e6a4-4969-9bc8-f67d60c1e229",
+          "source_id": "86665e90-ffbf-48fb-ad3f-e5d31fd50c51",
+          "sink_id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30",
+          "source_name": "result",
+          "sink_name": "value",
+          "is_static": false
+        },
+        {
+          "id": "20845dda-91de-4508-8077-0504b1a5ae03",
+          "source_id": "28bda769-b88b-44c9-be5c-52c2667f137e",
+          "sink_id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30",
+          "source_name": "result",
+          "sink_name": "value",
+          "is_static": false
+        },
+        {
+          "id": "6524c611-774b-45e9-899d-9a6aa80c549c",
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+          "sink_id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30",
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+          "sink_name": "value",
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+          "id": "714a0821-e5ba-4af7-9432-50491adda7b1",
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+          "sink_id": "5ac3727a-1ea7-436b-a902-ef1bfd883a30",
+          "source_name": "result",
+          "sink_name": "value",
+          "is_static": false
+        }
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+      "graph_id": "7b2e2095-782a-4f8d-adda-e62b661bccf5",
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+      "webhook": null
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+    {
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+      "block_id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
+      "input_default": {
+        "name": "Theme",
+        "value": "Cooking"
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+          "sink_id": "7543b9b0-0409-4cf8-bc4e-e0336273e2c4",
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+          "sink_name": "prompt_values_#_THEME",
+          "is_static": true
+        }
+      ],
+      "graph_id": "7b2e2095-782a-4f8d-adda-e62b661bccf5",
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+          "source_name": "response",
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+        }
+      ],
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+  "sub_graphs": [],
+  "user_id": "",
+  "created_at": "2024-12-20T19:58:34.390Z",
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+        "secret": false,
+        "title": "Theme",
+        "default": "Cooking"
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+    },
+    "required": []
+  },
+  "output_schema": {
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+    "properties": {
+      "Generated Image": {
+        "advanced": false,
+        "secret": false,
+        "title": "Generated Image",
+        "description": "The resulting generated image ready for you to review and post."
+      }
+    },
+    "required": [
+      "Generated Image"
+    ]
+  },
+  "has_external_trigger": false,
+  "has_human_in_the_loop": false,
+  "trigger_setup_info": null,
+  "credentials_input_schema": {
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+        "credentials_provider": [
+          "ideogram"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
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+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "ideogram",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.IDEOGRAM: 'ideogram'>], Literal['api_key']]",
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+        ],
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+          "api_key"
+        ],
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+          "id": {
+            "title": "Id",
+            "type": "string"
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+          "title": {
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+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "openai",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.OPENAI: 'openai'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator": "model",
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+          "Llama-3.3-8B-Instruct": "llama_api",
+          "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api",
+          "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api",
+          "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api",
+          "amazon/nova-lite-v1": "open_router",
+          "amazon/nova-micro-v1": "open_router",
+          "amazon/nova-pro-v1": "open_router",
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+          "claude-3-haiku-20240307": "anthropic",
+          "claude-haiku-4-5-20251001": "anthropic",
+          "claude-opus-4-1-20250805": "anthropic",
+          "claude-opus-4-20250514": "anthropic",
+          "claude-opus-4-5-20251101": "anthropic",
+          "claude-sonnet-4-20250514": "anthropic",
+          "claude-sonnet-4-5-20250929": "anthropic",
+          "cohere/command-r-08-2024": "open_router",
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+          "deepseek/deepseek-chat": "open_router",
+          "deepseek/deepseek-r1-0528": "open_router",
+          "dolphin-mistral:latest": "ollama",
+          "google/gemini-2.0-flash-001": "open_router",
+          "google/gemini-2.0-flash-lite-001": "open_router",
+          "google/gemini-2.5-flash": "open_router",
+          "google/gemini-2.5-flash-lite-preview-06-17": "open_router",
+          "google/gemini-2.5-pro-preview-03-25": "open_router",
+          "google/gemini-3-pro-preview": "open_router",
+          "gpt-3.5-turbo": "openai",
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+          "gpt-4o": "openai",
+          "gpt-4o-mini": "openai",
+          "gpt-5-2025-08-07": "openai",
+          "gpt-5-chat-latest": "openai",
+          "gpt-5-mini-2025-08-07": "openai",
+          "gpt-5-nano-2025-08-07": "openai",
+          "gpt-5.1-2025-11-13": "openai",
+          "gryphe/mythomax-l2-13b": "open_router",
+          "llama-3.1-8b-instant": "groq",
+          "llama-3.3-70b-versatile": "groq",
+          "llama3": "ollama",
+          "llama3.1:405b": "ollama",
+          "llama3.2": "ollama",
+          "llama3.3": "ollama",
+          "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/llama-4-maverick": "open_router",
+          "meta-llama/llama-4-scout": "open_router",
+          "microsoft/wizardlm-2-8x22b": "open_router",
+          "mistralai/mistral-nemo": "open_router",
+          "moonshotai/kimi-k2": "open_router",
+          "nousresearch/hermes-3-llama-3.1-405b": "open_router",
+          "nousresearch/hermes-3-llama-3.1-70b": "open_router",
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+          "o1": "openai",
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+          "o3-mini": "openai",
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+          "openai/gpt-oss-20b": "open_router",
+          "perplexity/sonar": "open_router",
+          "perplexity/sonar-deep-research": "open_router",
+          "perplexity/sonar-pro": "open_router",
+          "qwen/qwen3-235b-a22b-thinking-2507": "open_router",
+          "qwen/qwen3-coder": "open_router",
+          "v0-1.0-md": "v0",
+          "v0-1.5-lg": "v0",
+          "v0-1.5-md": "v0",
+          "x-ai/grok-4": "open_router",
+          "x-ai/grok-4-fast": "open_router",
+          "x-ai/grok-4.1-fast": "open_router",
+          "x-ai/grok-code-fast-1": "open_router"
+        },
+        "discriminator_values": [
+          "gpt-4o"
+        ]
+      }
+    },
+    "required": [
+      "ideogram_api_key_credentials",
+      "openai_api_key_credentials"
+    ],
+    "title": "UnspirationalPosterMakerCredentialsInputSchema",
+    "type": "object"
+  }
+}

autogpt_platform/backend/agents/agent_516d813b-d1bc-470f-add7-c63a4b2c2bad.json

@@ -0,0 +1,447 @@
+{
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+  "version": 18,
+  "is_active": true,
+  "name": "AI Function",
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+  "recommended_schedule_cron": null,
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+        "value": null,
+        "format": "",
+        "secret": false,
+        "advanced": false,
+        "description": "The value returned by the function"
+      },
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+          "y": 291.59140862204725
+        }
+      },
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+          "source_name": "response",
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+          "is_static": false
+        }
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+      "output_links": [],
+      "graph_id": "622849a7-5848-4838-894d-01f8f07e3fad",
+      "graph_version": 18,
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+      "webhook": null
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+      "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91",
+      "input_default": {
+        "model": "gpt-4o-mini",
+        "prompt": "Generate an incredibly detailed, photorealistic image prompt about {{TOPIC}}, describing the camera it's taken with and prompting the diffusion model to use all the best quality techniques.\n\nOutput only the prompt with no additional commentary.",
+        "prompt_values": {}
+      },
+      "metadata": {
+        "position": {
+          "x": 277.3057034159709,
+          "y": 962.8382498113764
+        }
+      },
+      "input_links": [
+        {
+          "id": "1077c61a-a32a-4ed7-becf-11bcf835b914",
+          "source_id": "6f24c45f-1548-4eda-9784-da06ce0abef8",
+          "sink_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12",
+          "source_name": "result",
+          "sink_name": "prompt_values_#_TOPIC",
+          "is_static": true
+        }
+      ],
+      "output_links": [
+        {
+          "id": "a17ec505-9377-4700-8fe0-124ca81d43a9",
+          "source_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12",
+          "sink_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea",
+          "source_name": "response",
+          "sink_name": "prompt",
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+        }
+      ],
+      "graph_id": "ed2091cf-5b27-45a9-b3ea-42396f95b256",
+      "graph_version": 12,
+      "webhook_id": null,
+      "webhook": null
+    }
+  ],
+  "links": [
+    {
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+      "source_id": "6f24c45f-1548-4eda-9784-da06ce0abef8",
+      "sink_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12",
+      "source_name": "result",
+      "sink_name": "prompt_values_#_TOPIC",
+      "is_static": true
+    },
+    {
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+      "source_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea",
+      "sink_id": "0d1dec1a-e4ee-4349-9673-449a01bbf14e",
+      "source_name": "result",
+      "sink_name": "value",
+      "is_static": false
+    },
+    {
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+      "source_id": "0d1bca9a-d9b8-4bfd-a19c-fe50b54f4b12",
+      "sink_id": "50bc23e9-f2b7-4959-8710-99679ed9eeea",
+      "source_name": "response",
+      "sink_name": "prompt",
+      "is_static": false
+    }
+  ],
+  "forked_from_id": null,
+  "forked_from_version": null,
+  "sub_graphs": [],
+  "user_id": "",
+  "created_at": "2024-12-20T18:46:11.492Z",
+  "input_schema": {
+    "type": "object",
+    "properties": {
+      "Image Subject": {
+        "advanced": false,
+        "secret": false,
+        "title": "Image Subject",
+        "description": "The subject of the image",
+        "default": "Otto the friendly, purple \"Chief Automation Octopus\" helping people automate their tedious tasks."
+      }
+    },
+    "required": []
+  },
+  "output_schema": {
+    "type": "object",
+    "properties": {
+      "Generated Image": {
+        "advanced": false,
+        "secret": false,
+        "title": "Generated Image"
+      }
+    },
+    "required": [
+      "Generated Image"
+    ]
+  },
+  "has_external_trigger": false,
+  "has_human_in_the_loop": false,
+  "trigger_setup_info": null,
+  "credentials_input_schema": {
+    "properties": {
+      "replicate_api_key_credentials": {
+        "credentials_provider": [
+          "replicate"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
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+            "type": "string"
+          },
+          "title": {
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+              },
+              {
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+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "replicate",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.REPLICATE: 'replicate'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator_values": []
+      },
+      "openai_api_key_credentials": {
+        "credentials_provider": [
+          "openai"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "openai",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.OPENAI: 'openai'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator": "model",
+        "discriminator_mapping": {
+          "Llama-3.3-70B-Instruct": "llama_api",
+          "Llama-3.3-8B-Instruct": "llama_api",
+          "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api",
+          "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api",
+          "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api",
+          "amazon/nova-lite-v1": "open_router",
+          "amazon/nova-micro-v1": "open_router",
+          "amazon/nova-pro-v1": "open_router",
+          "claude-3-7-sonnet-20250219": "anthropic",
+          "claude-3-haiku-20240307": "anthropic",
+          "claude-haiku-4-5-20251001": "anthropic",
+          "claude-opus-4-1-20250805": "anthropic",
+          "claude-opus-4-20250514": "anthropic",
+          "claude-opus-4-5-20251101": "anthropic",
+          "claude-sonnet-4-20250514": "anthropic",
+          "claude-sonnet-4-5-20250929": "anthropic",
+          "cohere/command-r-08-2024": "open_router",
+          "cohere/command-r-plus-08-2024": "open_router",
+          "deepseek/deepseek-chat": "open_router",
+          "deepseek/deepseek-r1-0528": "open_router",
+          "dolphin-mistral:latest": "ollama",
+          "google/gemini-2.0-flash-001": "open_router",
+          "google/gemini-2.0-flash-lite-001": "open_router",
+          "google/gemini-2.5-flash": "open_router",
+          "google/gemini-2.5-flash-lite-preview-06-17": "open_router",
+          "google/gemini-2.5-pro-preview-03-25": "open_router",
+          "google/gemini-3-pro-preview": "open_router",
+          "gpt-3.5-turbo": "openai",
+          "gpt-4-turbo": "openai",
+          "gpt-4.1-2025-04-14": "openai",
+          "gpt-4.1-mini-2025-04-14": "openai",
+          "gpt-4o": "openai",
+          "gpt-4o-mini": "openai",
+          "gpt-5-2025-08-07": "openai",
+          "gpt-5-chat-latest": "openai",
+          "gpt-5-mini-2025-08-07": "openai",
+          "gpt-5-nano-2025-08-07": "openai",
+          "gpt-5.1-2025-11-13": "openai",
+          "gryphe/mythomax-l2-13b": "open_router",
+          "llama-3.1-8b-instant": "groq",
+          "llama-3.3-70b-versatile": "groq",
+          "llama3": "ollama",
+          "llama3.1:405b": "ollama",
+          "llama3.2": "ollama",
+          "llama3.3": "ollama",
+          "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/llama-4-maverick": "open_router",
+          "meta-llama/llama-4-scout": "open_router",
+          "microsoft/wizardlm-2-8x22b": "open_router",
+          "mistralai/mistral-nemo": "open_router",
+          "moonshotai/kimi-k2": "open_router",
+          "nousresearch/hermes-3-llama-3.1-405b": "open_router",
+          "nousresearch/hermes-3-llama-3.1-70b": "open_router",
+          "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api",
+          "o1": "openai",
+          "o1-mini": "openai",
+          "o3-2025-04-16": "openai",
+          "o3-mini": "openai",
+          "openai/gpt-oss-120b": "open_router",
+          "openai/gpt-oss-20b": "open_router",
+          "perplexity/sonar": "open_router",
+          "perplexity/sonar-deep-research": "open_router",
+          "perplexity/sonar-pro": "open_router",
+          "qwen/qwen3-235b-a22b-thinking-2507": "open_router",
+          "qwen/qwen3-coder": "open_router",
+          "v0-1.0-md": "v0",
+          "v0-1.5-lg": "v0",
+          "v0-1.5-md": "v0",
+          "x-ai/grok-4": "open_router",
+          "x-ai/grok-4-fast": "open_router",
+          "x-ai/grok-4.1-fast": "open_router",
+          "x-ai/grok-code-fast-1": "open_router"
+        },
+        "discriminator_values": [
+          "gpt-4o-mini"
+        ]
+      }
+    },
+    "required": [
+      "replicate_api_key_credentials",
+      "openai_api_key_credentials"
+    ],
+    "title": "FluxAIImageGeneratorCredentialsInputSchema",
+    "type": "object"
+  }
+}

autogpt_platform/backend/agents/agent_f2cc74bb-f43f-4395-9c35-ecb30b5b4fc9.json

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+      "sink_name": "prompt_values_#_CONTENT",
+      "is_static": false
+    },
+    {
+      "id": "d4334477-3616-454f-a430-614ca27f5b36",
+      "source_id": "c9924577-70d8-4ccb-9106-6f796df09ef9",
+      "sink_id": "130ec496-f75d-4fe2-9cd6-8c00d08ea4a7",
+      "source_name": "response",
+      "sink_name": "value",
+      "is_static": false
+    },
+    {
+      "id": "5d5656fd-4208-4296-bc70-e39cc31caada",
+      "source_id": "b40595c6-dba3-4779-a129-cd4f01fff103",
+      "sink_id": "08612ce2-625b-4c17-accd-3acace7b6477",
+      "source_name": "content",
+      "sink_name": "prompt_values_#_CONTENT",
+      "is_static": false
+    },
+    {
+      "id": "f979ab78-0903-4f19-a7c2-a419d5d81aef",
+      "source_id": "08612ce2-625b-4c17-accd-3acace7b6477",
+      "sink_id": "cefccd07-fe70-4feb-bf76-46b20aaa5d35",
+      "source_name": "response",
+      "sink_name": "value",
+      "is_static": false
+    },
+    {
+      "id": "6bcca45d-c9d5-439e-ac43-e4a1264d8f57",
+      "source_id": "08612ce2-625b-4c17-accd-3acace7b6477",
+      "sink_id": "c9924577-70d8-4ccb-9106-6f796df09ef9",
+      "source_name": "response",
+      "sink_name": "prompt_values_#_ANALYSIS",
+      "is_static": false
+    },
+    {
+      "id": "cbb12335-fefd-4560-9fff-98675130fbad",
+      "source_id": "375f8bc3-afd9-4025-ad8e-9aeb329af7ce",
+      "sink_id": "b40595c6-dba3-4779-a129-cd4f01fff103",
+      "source_name": "result",
+      "sink_name": "url",
+      "is_static": true
+    }
+  ],
+  "forked_from_id": null,
+  "forked_from_version": null,
+  "sub_graphs": [],
+  "user_id": "",
+  "created_at": "2024-12-20T19:47:22.036Z",
+  "input_schema": {
+    "type": "object",
+    "properties": {
+      "Homepage URL": {
+        "advanced": false,
+        "secret": false,
+        "title": "Homepage URL",
+        "description": "Enter the URL of the homepage you want to improve",
+        "default": "https://agpt.co"
+      }
+    },
+    "required": []
+  },
+  "output_schema": {
+    "type": "object",
+    "properties": {
+      "Improved Webpage Copy": {
+        "advanced": false,
+        "secret": false,
+        "title": "Improved Webpage Copy"
+      },
+      "Original Page Analysis": {
+        "advanced": false,
+        "secret": false,
+        "title": "Original Page Analysis",
+        "description": "Analysis of the webpage as it currently stands."
+      }
+    },
+    "required": [
+      "Improved Webpage Copy",
+      "Original Page Analysis"
+    ]
+  },
+  "has_external_trigger": false,
+  "has_human_in_the_loop": false,
+  "trigger_setup_info": null,
+  "credentials_input_schema": {
+    "properties": {
+      "jina_api_key_credentials": {
+        "credentials_provider": [
+          "jina"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "jina",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.JINA: 'jina'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator_values": []
+      },
+      "openai_api_key_credentials": {
+        "credentials_provider": [
+          "openai"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "openai",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.OPENAI: 'openai'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator": "model",
+        "discriminator_mapping": {
+          "Llama-3.3-70B-Instruct": "llama_api",
+          "Llama-3.3-8B-Instruct": "llama_api",
+          "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api",
+          "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api",
+          "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api",
+          "amazon/nova-lite-v1": "open_router",
+          "amazon/nova-micro-v1": "open_router",
+          "amazon/nova-pro-v1": "open_router",
+          "claude-3-7-sonnet-20250219": "anthropic",
+          "claude-3-haiku-20240307": "anthropic",
+          "claude-haiku-4-5-20251001": "anthropic",
+          "claude-opus-4-1-20250805": "anthropic",
+          "claude-opus-4-20250514": "anthropic",
+          "claude-opus-4-5-20251101": "anthropic",
+          "claude-sonnet-4-20250514": "anthropic",
+          "claude-sonnet-4-5-20250929": "anthropic",
+          "cohere/command-r-08-2024": "open_router",
+          "cohere/command-r-plus-08-2024": "open_router",
+          "deepseek/deepseek-chat": "open_router",
+          "deepseek/deepseek-r1-0528": "open_router",
+          "dolphin-mistral:latest": "ollama",
+          "google/gemini-2.0-flash-001": "open_router",
+          "google/gemini-2.0-flash-lite-001": "open_router",
+          "google/gemini-2.5-flash": "open_router",
+          "google/gemini-2.5-flash-lite-preview-06-17": "open_router",
+          "google/gemini-2.5-pro-preview-03-25": "open_router",
+          "google/gemini-3-pro-preview": "open_router",
+          "gpt-3.5-turbo": "openai",
+          "gpt-4-turbo": "openai",
+          "gpt-4.1-2025-04-14": "openai",
+          "gpt-4.1-mini-2025-04-14": "openai",
+          "gpt-4o": "openai",
+          "gpt-4o-mini": "openai",
+          "gpt-5-2025-08-07": "openai",
+          "gpt-5-chat-latest": "openai",
+          "gpt-5-mini-2025-08-07": "openai",
+          "gpt-5-nano-2025-08-07": "openai",
+          "gpt-5.1-2025-11-13": "openai",
+          "gryphe/mythomax-l2-13b": "open_router",
+          "llama-3.1-8b-instant": "groq",
+          "llama-3.3-70b-versatile": "groq",
+          "llama3": "ollama",
+          "llama3.1:405b": "ollama",
+          "llama3.2": "ollama",
+          "llama3.3": "ollama",
+          "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/llama-4-maverick": "open_router",
+          "meta-llama/llama-4-scout": "open_router",
+          "microsoft/wizardlm-2-8x22b": "open_router",
+          "mistralai/mistral-nemo": "open_router",
+          "moonshotai/kimi-k2": "open_router",
+          "nousresearch/hermes-3-llama-3.1-405b": "open_router",
+          "nousresearch/hermes-3-llama-3.1-70b": "open_router",
+          "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api",
+          "o1": "openai",
+          "o1-mini": "openai",
+          "o3-2025-04-16": "openai",
+          "o3-mini": "openai",
+          "openai/gpt-oss-120b": "open_router",
+          "openai/gpt-oss-20b": "open_router",
+          "perplexity/sonar": "open_router",
+          "perplexity/sonar-deep-research": "open_router",
+          "perplexity/sonar-pro": "open_router",
+          "qwen/qwen3-235b-a22b-thinking-2507": "open_router",
+          "qwen/qwen3-coder": "open_router",
+          "v0-1.0-md": "v0",
+          "v0-1.5-lg": "v0",
+          "v0-1.5-md": "v0",
+          "x-ai/grok-4": "open_router",
+          "x-ai/grok-4-fast": "open_router",
+          "x-ai/grok-4.1-fast": "open_router",
+          "x-ai/grok-code-fast-1": "open_router"
+        },
+        "discriminator_values": [
+          "gpt-4o"
+        ]
+      }
+    },
+    "required": [
+      "jina_api_key_credentials",
+      "openai_api_key_credentials"
+    ],
+    "title": "AIWebpageCopyImproverCredentialsInputSchema",
+    "type": "object"
+  }
+}

autogpt_platform/backend/agents/agent_fc2c9976-0962-4625-a27b-d316573a9e7f.json

@@ -0,0 +1,615 @@
+{
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+      "block_id": "1f292d4a-41a4-4977-9684-7c8d560b9f91",
+      "input_default": {
+        "model": "claude-sonnet-4-5-20250929",
+        "prompt": "<business_website>\n{{WEBSITE_CONTENT}}\n</business_website>\n\nExtract the Contact Email of {{BUSINESS_NAME}}.\n\nIf no email that can be used to contact {{BUSINESS_NAME}} is present, output `N/A`.\nDo not share any emails other than the email for this specific entity.\n\nIf multiple present pick the likely best one.\n\nRespond with the email (or N/A) inside <email></email> tags.\n\nExample Response:\n\n<thoughts_or_comments>\nThere were many emails present, but luckily one was for {{BUSINESS_NAME}} which I have included below.\n</thoughts_or_comments>\n<email>\nexample@email.com\n</email>",
+        "prompt_values": {}
+      },
+      "metadata": {
+        "position": {
+          "x": 2774.879259081777,
+          "y": 243.3102035752969
+        }
+      },
+      "input_links": [
+        {
+          "id": "43e920a7-0bb4-4fae-9a22-91df95c7342a",
+          "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794",
+          "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+          "source_name": "result",
+          "sink_name": "prompt_values_#_BUSINESS_NAME",
+          "is_static": true
+        },
+        {
+          "id": "899cc7d8-a96b-4107-b3c6-4c78edcf0c6b",
+          "source_id": "4a41df99-ffe2-4c12-b528-632979c9c030",
+          "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+          "source_name": "results",
+          "sink_name": "prompt_values_#_WEBSITE_CONTENT",
+          "is_static": false
+        }
+      ],
+      "output_links": [
+        {
+          "id": "9f8188ce-1f3d-46fb-acda-b2a57c0e5da6",
+          "source_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+          "sink_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981",
+          "source_name": "response",
+          "sink_name": "text",
+          "is_static": false
+        }
+      ],
+      "graph_id": "4c6b68cb-bb75-4044-b1cb-2cee3fd39b26",
+      "graph_version": 29,
+      "webhook_id": null,
+      "webhook": null
+    }
+  ],
+  "links": [
+    {
+      "id": "9f8188ce-1f3d-46fb-acda-b2a57c0e5da6",
+      "source_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+      "sink_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981",
+      "source_name": "response",
+      "sink_name": "text",
+      "is_static": false
+    },
+    {
+      "id": "b15b5143-27b7-486e-a166-4095e72e5235",
+      "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981",
+      "sink_id": "266b7255-11c4-4b88-99e2-85db31a2e865",
+      "source_name": "negative",
+      "sink_name": "values_#_Result",
+      "is_static": false
+    },
+    {
+      "id": "d87b07ea-dcec-4d38-a644-2c1d741ea3cb",
+      "source_id": "266b7255-11c4-4b88-99e2-85db31a2e865",
+      "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130",
+      "source_name": "output",
+      "sink_name": "value",
+      "is_static": false
+    },
+    {
+      "id": "946b522c-365f-4ee0-96f9-28863d9882ea",
+      "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794",
+      "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694",
+      "source_name": "result",
+      "sink_name": "values_#_NAME",
+      "is_static": true
+    },
+    {
+      "id": "23591872-3c6b-4562-87d3-5b6ade698e48",
+      "source_id": "a6e7355e-5bf8-4b09-b11c-a5e140389981",
+      "sink_id": "310c8fab-2ae6-4158-bd48-01dbdc434130",
+      "source_name": "positive",
+      "sink_name": "value",
+      "is_static": false
+    },
+    {
+      "id": "43e920a7-0bb4-4fae-9a22-91df95c7342a",
+      "source_id": "9708a10a-8be0-4c44-abb3-bd0f7c594794",
+      "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+      "source_name": "result",
+      "sink_name": "prompt_values_#_BUSINESS_NAME",
+      "is_static": true
+    },
+    {
+      "id": "2e411d3d-79ba-4958-9c1c-b76a45a2e649",
+      "source_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694",
+      "sink_id": "4a41df99-ffe2-4c12-b528-632979c9c030",
+      "source_name": "output",
+      "sink_name": "query",
+      "is_static": false
+    },
+    {
+      "id": "aac29f7b-3cd1-4c91-9a2a-72a8301c0957",
+      "source_id": "04cad535-9f1a-4876-8b07-af5897d8c282",
+      "sink_id": "28b5ddcc-dc20-41cc-ad21-c54ff459f694",
+      "source_name": "result",
+      "sink_name": "values_#_ADDRESS",
+      "is_static": true
+    },
+    {
+      "id": "899cc7d8-a96b-4107-b3c6-4c78edcf0c6b",
+      "source_id": "4a41df99-ffe2-4c12-b528-632979c9c030",
+      "sink_id": "510937b3-0134-4e45-b2ba-05a447bbaf50",
+      "source_name": "results",
+      "sink_name": "prompt_values_#_WEBSITE_CONTENT",
+      "is_static": false
+    }
+  ],
+  "forked_from_id": null,
+  "forked_from_version": null,
+  "sub_graphs": [],
+  "user_id": "",
+  "created_at": "2025-01-03T00:46:30.244Z",
+  "input_schema": {
+    "type": "object",
+    "properties": {
+      "Address": {
+        "advanced": false,
+        "secret": false,
+        "title": "Address",
+        "default": "USA"
+      },
+      "Business Name": {
+        "advanced": false,
+        "secret": false,
+        "title": "Business Name",
+        "default": "Tim Cook"
+      }
+    },
+    "required": []
+  },
+  "output_schema": {
+    "type": "object",
+    "properties": {
+      "Email": {
+        "advanced": false,
+        "secret": false,
+        "title": "Email"
+      }
+    },
+    "required": [
+      "Email"
+    ]
+  },
+  "has_external_trigger": false,
+  "has_human_in_the_loop": false,
+  "trigger_setup_info": null,
+  "credentials_input_schema": {
+    "properties": {
+      "jina_api_key_credentials": {
+        "credentials_provider": [
+          "jina"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "jina",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.JINA: 'jina'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator_values": []
+      },
+      "anthropic_api_key_credentials": {
+        "credentials_provider": [
+          "anthropic"
+        ],
+        "credentials_types": [
+          "api_key"
+        ],
+        "properties": {
+          "id": {
+            "title": "Id",
+            "type": "string"
+          },
+          "title": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "title": "Title"
+          },
+          "provider": {
+            "const": "anthropic",
+            "title": "Provider",
+            "type": "string"
+          },
+          "type": {
+            "const": "api_key",
+            "title": "Type",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "provider",
+          "type"
+        ],
+        "title": "CredentialsMetaInput[Literal[<ProviderName.ANTHROPIC: 'anthropic'>], Literal['api_key']]",
+        "type": "object",
+        "discriminator": "model",
+        "discriminator_mapping": {
+          "Llama-3.3-70B-Instruct": "llama_api",
+          "Llama-3.3-8B-Instruct": "llama_api",
+          "Llama-4-Maverick-17B-128E-Instruct-FP8": "llama_api",
+          "Llama-4-Scout-17B-16E-Instruct-FP8": "llama_api",
+          "Qwen/Qwen2.5-72B-Instruct-Turbo": "aiml_api",
+          "amazon/nova-lite-v1": "open_router",
+          "amazon/nova-micro-v1": "open_router",
+          "amazon/nova-pro-v1": "open_router",
+          "claude-3-7-sonnet-20250219": "anthropic",
+          "claude-3-haiku-20240307": "anthropic",
+          "claude-haiku-4-5-20251001": "anthropic",
+          "claude-opus-4-1-20250805": "anthropic",
+          "claude-opus-4-20250514": "anthropic",
+          "claude-opus-4-5-20251101": "anthropic",
+          "claude-sonnet-4-20250514": "anthropic",
+          "claude-sonnet-4-5-20250929": "anthropic",
+          "cohere/command-r-08-2024": "open_router",
+          "cohere/command-r-plus-08-2024": "open_router",
+          "deepseek/deepseek-chat": "open_router",
+          "deepseek/deepseek-r1-0528": "open_router",
+          "dolphin-mistral:latest": "ollama",
+          "google/gemini-2.0-flash-001": "open_router",
+          "google/gemini-2.0-flash-lite-001": "open_router",
+          "google/gemini-2.5-flash": "open_router",
+          "google/gemini-2.5-flash-lite-preview-06-17": "open_router",
+          "google/gemini-2.5-pro-preview-03-25": "open_router",
+          "google/gemini-3-pro-preview": "open_router",
+          "gpt-3.5-turbo": "openai",
+          "gpt-4-turbo": "openai",
+          "gpt-4.1-2025-04-14": "openai",
+          "gpt-4.1-mini-2025-04-14": "openai",
+          "gpt-4o": "openai",
+          "gpt-4o-mini": "openai",
+          "gpt-5-2025-08-07": "openai",
+          "gpt-5-chat-latest": "openai",
+          "gpt-5-mini-2025-08-07": "openai",
+          "gpt-5-nano-2025-08-07": "openai",
+          "gpt-5.1-2025-11-13": "openai",
+          "gryphe/mythomax-l2-13b": "open_router",
+          "llama-3.1-8b-instant": "groq",
+          "llama-3.3-70b-versatile": "groq",
+          "llama3": "ollama",
+          "llama3.1:405b": "ollama",
+          "llama3.2": "ollama",
+          "llama3.3": "ollama",
+          "meta-llama/Llama-3.2-3B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Llama-3.3-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": "aiml_api",
+          "meta-llama/llama-4-maverick": "open_router",
+          "meta-llama/llama-4-scout": "open_router",
+          "microsoft/wizardlm-2-8x22b": "open_router",
+          "mistralai/mistral-nemo": "open_router",
+          "moonshotai/kimi-k2": "open_router",
+          "nousresearch/hermes-3-llama-3.1-405b": "open_router",
+          "nousresearch/hermes-3-llama-3.1-70b": "open_router",
+          "nvidia/llama-3.1-nemotron-70b-instruct": "aiml_api",
+          "o1": "openai",
+          "o1-mini": "openai",
+          "o3-2025-04-16": "openai",
+          "o3-mini": "openai",
+          "openai/gpt-oss-120b": "open_router",
+          "openai/gpt-oss-20b": "open_router",
+          "perplexity/sonar": "open_router",
+          "perplexity/sonar-deep-research": "open_router",
+          "perplexity/sonar-pro": "open_router",
+          "qwen/qwen3-235b-a22b-thinking-2507": "open_router",
+          "qwen/qwen3-coder": "open_router",
+          "v0-1.0-md": "v0",
+          "v0-1.5-lg": "v0",
+          "v0-1.5-md": "v0",
+          "x-ai/grok-4": "open_router",
+          "x-ai/grok-4-fast": "open_router",
+          "x-ai/grok-4.1-fast": "open_router",
+          "x-ai/grok-code-fast-1": "open_router"
+        },
+        "discriminator_values": [
+          "claude-sonnet-4-5-20250929"
+        ]
+      }
+    },
+    "required": [
+      "jina_api_key_credentials",
+      "anthropic_api_key_credentials"
+    ],
+    "title": "EmailAddressFinderCredentialsInputSchema",
+    "type": "object"
+  }
+}

autogpt_platform/backend/backend/api/conn_manager.py

@@ -3,12 +3,12 @@ from typing import Dict, Set
 
 from fastapi import WebSocket
 
+from backend.api.model import NotificationPayload, WSMessage, WSMethod
 from backend.data.execution import (
     ExecutionEventType,
     GraphExecutionEvent,
     NodeExecutionEvent,
 )
-from backend.server.model import NotificationPayload, WSMessage, WSMethod
 
 _EVENT_TYPE_TO_METHOD_MAP: dict[ExecutionEventType, WSMethod] = {
     ExecutionEventType.GRAPH_EXEC_UPDATE: WSMethod.GRAPH_EXECUTION_EVENT,

autogpt_platform/backend/backend/api/conn_manager_test.py

@@ -4,13 +4,13 @@ from unittest.mock import AsyncMock
 import pytest
 from fastapi import WebSocket
 
+from backend.api.conn_manager import ConnectionManager
+from backend.api.model import NotificationPayload, WSMessage, WSMethod
 from backend.data.execution import (
     ExecutionStatus,
     GraphExecutionEvent,
     NodeExecutionEvent,
 )
-from backend.server.conn_manager import ConnectionManager
-from backend.server.model import NotificationPayload, WSMessage, WSMethod
 
 
 @pytest.fixture

autogpt_platform/backend/backend/api/external/fastapi_app.py

@@ -1,23 +1,23 @@
 from fastapi import FastAPI
 
+from backend.api.middleware.security import SecurityHeadersMiddleware
 from backend.monitoring.instrumentation import instrument_fastapi
-from backend.server.middleware.security import SecurityHeadersMiddleware
 
-from .routes.v1 import v1_router
+from .v1.routes import v1_router
 
-external_app = FastAPI(
+external_api = FastAPI(
     title="AutoGPT External API",
     description="External API for AutoGPT integrations",
     docs_url="/docs",
     version="1.0",
 )
 
-external_app.add_middleware(SecurityHeadersMiddleware)
-external_app.include_router(v1_router, prefix="/v1")
+external_api.add_middleware(SecurityHeadersMiddleware)
+external_api.include_router(v1_router, prefix="/v1")
 
 # Add Prometheus instrumentation
 instrument_fastapi(
-    external_app,
+    external_api,
     service_name="external-api",
     expose_endpoint=True,
     endpoint="/metrics",

autogpt_platform/backend/backend/api/external/middleware.py

@@ -0,0 +1,107 @@
+from fastapi import HTTPException, Security, status
+from fastapi.security import APIKeyHeader, HTTPAuthorizationCredentials, HTTPBearer
+from prisma.enums import APIKeyPermission
+
+from backend.data.auth.api_key import APIKeyInfo, validate_api_key
+from backend.data.auth.base import APIAuthorizationInfo
+from backend.data.auth.oauth import (
+    InvalidClientError,
+    InvalidTokenError,
+    OAuthAccessTokenInfo,
+    validate_access_token,
+)
+
+api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
+bearer_auth = HTTPBearer(auto_error=False)
+
+
+async def require_api_key(api_key: str | None = Security(api_key_header)) -> APIKeyInfo:
+    """Middleware for API key authentication only"""
+    if api_key is None:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Missing API key"
+        )
+
+    api_key_obj = await validate_api_key(api_key)
+
+    if not api_key_obj:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
+        )
+
+    return api_key_obj
+
+
+async def require_access_token(
+    bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
+) -> OAuthAccessTokenInfo:
+    """Middleware for OAuth access token authentication only"""
+    if bearer is None:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Missing Authorization header",
+        )
+
+    try:
+        token_info, _ = await validate_access_token(bearer.credentials)
+    except (InvalidClientError, InvalidTokenError) as e:
+        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
+
+    return token_info
+
+
+async def require_auth(
+    api_key: str | None = Security(api_key_header),
+    bearer: HTTPAuthorizationCredentials | None = Security(bearer_auth),
+) -> APIAuthorizationInfo:
+    """
+    Unified authentication middleware supporting both API keys and OAuth tokens.
+
+    Supports two authentication methods, which are checked in order:
+    1. X-API-Key header (existing API key authentication)
+    2. Authorization: Bearer <token> header (OAuth access token)
+
+    Returns:
+        APIAuthorizationInfo: base class of both APIKeyInfo and OAuthAccessTokenInfo.
+    """
+    # Try API key first
+    if api_key is not None:
+        api_key_info = await validate_api_key(api_key)
+        if api_key_info:
+            return api_key_info
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key"
+        )
+
+    # Try OAuth bearer token
+    if bearer is not None:
+        try:
+            token_info, _ = await validate_access_token(bearer.credentials)
+            return token_info
+        except (InvalidClientError, InvalidTokenError) as e:
+            raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=str(e))
+
+    # No credentials provided
+    raise HTTPException(
+        status_code=status.HTTP_401_UNAUTHORIZED,
+        detail="Missing authentication. Provide API key or access token.",
+    )
+
+
+def require_permission(permission: APIKeyPermission):
+    """
+    Dependency function for checking specific permissions
+    (works with API keys and OAuth tokens)
+    """
+
+    async def check_permission(
+        auth: APIAuthorizationInfo = Security(require_auth),
+    ) -> APIAuthorizationInfo:
+        if permission not in auth.scopes:
+            raise HTTPException(
+                status_code=status.HTTP_403_FORBIDDEN,
+                detail=f"Missing required permission: {permission.value}",
+            )
+        return auth
+
+    return check_permission

autogpt_platform/backend/backend/api/external/v1/integrations.py

@@ -0,0 +1,655 @@
+"""
+External API endpoints for integrations and credentials.
+
+This module provides endpoints for external applications (like Autopilot) to:
+- Initiate OAuth flows with custom callback URLs
+- Complete OAuth flows by exchanging authorization codes
+- Create API key, user/password, and host-scoped credentials
+- List and manage user credentials
+"""
+
+import logging
+from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, Union
+from urllib.parse import urlparse
+
+from fastapi import APIRouter, Body, HTTPException, Path, Security, status
+from prisma.enums import APIKeyPermission
+from pydantic import BaseModel, Field, SecretStr
+
+from backend.api.external.middleware import require_permission
+from backend.api.features.integrations.models import get_all_provider_names
+from backend.data.auth.base import APIAuthorizationInfo
+from backend.data.model import (
+    APIKeyCredentials,
+    Credentials,
+    CredentialsType,
+    HostScopedCredentials,
+    OAuth2Credentials,
+    UserPasswordCredentials,
+)
+from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
+from backend.integrations.providers import ProviderName
+from backend.util.settings import Settings
+
+if TYPE_CHECKING:
+    from backend.integrations.oauth import BaseOAuthHandler
+
+logger = logging.getLogger(__name__)
+settings = Settings()
+creds_manager = IntegrationCredentialsManager()
+
+integrations_router = APIRouter(prefix="/integrations", tags=["integrations"])
+
+
+# ==================== Request/Response Models ==================== #
+
+
+class OAuthInitiateRequest(BaseModel):
+    """Request model for initiating an OAuth flow."""
+
+    callback_url: str = Field(
+        ..., description="The external app's callback URL for OAuth redirect"
+    )
+    scopes: list[str] = Field(
+        default_factory=list, description="OAuth scopes to request"
+    )
+    state_metadata: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Arbitrary metadata to echo back on completion",
+    )
+
+
+class OAuthInitiateResponse(BaseModel):
+    """Response model for OAuth initiation."""
+
+    login_url: str = Field(..., description="URL to redirect user for OAuth consent")
+    state_token: str = Field(..., description="State token for CSRF protection")
+    expires_at: int = Field(
+        ..., description="Unix timestamp when the state token expires"
+    )
+
+
+class OAuthCompleteRequest(BaseModel):
+    """Request model for completing an OAuth flow."""
+
+    code: str = Field(..., description="Authorization code from OAuth provider")
+    state_token: str = Field(..., description="State token from initiate request")
+
+
+class OAuthCompleteResponse(BaseModel):
+    """Response model for OAuth completion."""
+
+    credentials_id: str = Field(..., description="ID of the stored credentials")
+    provider: str = Field(..., description="Provider name")
+    type: str = Field(..., description="Credential type (oauth2)")
+    title: Optional[str] = Field(None, description="Credential title")
+    scopes: list[str] = Field(default_factory=list, description="Granted scopes")
+    username: Optional[str] = Field(None, description="Username from provider")
+    state_metadata: dict[str, Any] = Field(
+        default_factory=dict, description="Echoed metadata from initiate request"
+    )
+
+
+class CredentialSummary(BaseModel):
+    """Summary of a credential without sensitive data."""
+
+    id: str
+    provider: str
+    type: CredentialsType
+    title: Optional[str] = None
+    scopes: Optional[list[str]] = None
+    username: Optional[str] = None
+    host: Optional[str] = None
+
+
+class ProviderInfo(BaseModel):
+    """Information about an integration provider."""
+
+    name: str
+    supports_oauth: bool = False
+    supports_api_key: bool = False
+    supports_user_password: bool = False
+    supports_host_scoped: bool = False
+    default_scopes: list[str] = Field(default_factory=list)
+
+
+# ==================== Credential Creation Models ==================== #
+
+
+class CreateAPIKeyCredentialRequest(BaseModel):
+    """Request model for creating API key credentials."""
+
+    type: Literal["api_key"] = "api_key"
+    api_key: str = Field(..., description="The API key")
+    title: str = Field(..., description="A name for this credential")
+    expires_at: Optional[int] = Field(
+        None, description="Unix timestamp when the API key expires"
+    )
+
+
+class CreateUserPasswordCredentialRequest(BaseModel):
+    """Request model for creating username/password credentials."""
+
+    type: Literal["user_password"] = "user_password"
+    username: str = Field(..., description="Username")
+    password: str = Field(..., description="Password")
+    title: str = Field(..., description="A name for this credential")
+
+
+class CreateHostScopedCredentialRequest(BaseModel):
+    """Request model for creating host-scoped credentials."""
+
+    type: Literal["host_scoped"] = "host_scoped"
+    host: str = Field(..., description="Host/domain pattern to match")
+    headers: dict[str, str] = Field(..., description="Headers to include in requests")
+    title: str = Field(..., description="A name for this credential")
+
+
+# Union type for credential creation
+CreateCredentialRequest = Annotated[
+    CreateAPIKeyCredentialRequest
+    | CreateUserPasswordCredentialRequest
+    | CreateHostScopedCredentialRequest,
+    Field(discriminator="type"),
+]
+
+
+class CreateCredentialResponse(BaseModel):
+    """Response model for credential creation."""
+
+    id: str
+    provider: str
+    type: CredentialsType
+    title: Optional[str] = None
+
+
+# ==================== Helper Functions ==================== #
+
+
+def validate_callback_url(callback_url: str) -> bool:
+    """Validate that the callback URL is from an allowed origin."""
+    allowed_origins = settings.config.external_oauth_callback_origins
+
+    try:
+        parsed = urlparse(callback_url)
+        callback_origin = f"{parsed.scheme}://{parsed.netloc}"
+
+        for allowed in allowed_origins:
+            # Simple origin matching
+            if callback_origin == allowed:
+                return True
+
+        # Allow localhost with any port in development (proper hostname check)
+        if parsed.hostname == "localhost":
+            for allowed in allowed_origins:
+                allowed_parsed = urlparse(allowed)
+                if allowed_parsed.hostname == "localhost":
+                    return True
+
+        return False
+    except Exception:
+        return False
+
+
+def _get_oauth_handler_for_external(
+    provider_name: str, redirect_uri: str
+) -> "BaseOAuthHandler":
+    """Get an OAuth handler configured with an external redirect URI."""
+    # Ensure blocks are loaded so SDK providers are available
+    try:
+        from backend.blocks import load_all_blocks
+
+        load_all_blocks()
+    except Exception as e:
+        logger.warning(f"Failed to load blocks: {e}")
+
+    if provider_name not in HANDLERS_BY_NAME:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Provider '{provider_name}' does not support OAuth",
+        )
+
+    # Check if this provider has custom OAuth credentials
+    oauth_credentials = CREDENTIALS_BY_PROVIDER.get(provider_name)
+
+    if oauth_credentials and not oauth_credentials.use_secrets:
+        import os
+
+        client_id = (
+            os.getenv(oauth_credentials.client_id_env_var)
+            if oauth_credentials.client_id_env_var
+            else None
+        )
+        client_secret = (
+            os.getenv(oauth_credentials.client_secret_env_var)
+            if oauth_credentials.client_secret_env_var
+            else None
+        )
+    else:
+        client_id = getattr(settings.secrets, f"{provider_name}_client_id", None)
+        client_secret = getattr(
+            settings.secrets, f"{provider_name}_client_secret", None
+        )
+
+    if not (client_id and client_secret):
+        logger.error(f"Attempt to use unconfigured {provider_name} OAuth integration")
+        raise HTTPException(
+            status_code=status.HTTP_501_NOT_IMPLEMENTED,
+            detail={
+                "message": f"Integration with provider '{provider_name}' is not configured.",
+                "hint": "Set client ID and secret in the application's deployment environment",
+            },
+        )
+
+    handler_class = HANDLERS_BY_NAME[provider_name]
+    return handler_class(
+        client_id=client_id,
+        client_secret=client_secret,
+        redirect_uri=redirect_uri,
+    )
+
+
+# ==================== Endpoints ==================== #
+
+
+@integrations_router.get("/providers", response_model=list[ProviderInfo])
+async def list_providers(
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.READ_INTEGRATIONS)
+    ),
+) -> list[ProviderInfo]:
+    """
+    List all available integration providers.
+
+    Returns a list of all providers with their supported credential types.
+    Most providers support API key credentials, and some also support OAuth.
+    """
+    # Ensure blocks are loaded
+    try:
+        from backend.blocks import load_all_blocks
+
+        load_all_blocks()
+    except Exception as e:
+        logger.warning(f"Failed to load blocks: {e}")
+
+    from backend.sdk.registry import AutoRegistry
+
+    providers = []
+    for name in get_all_provider_names():
+        supports_oauth = name in HANDLERS_BY_NAME
+        handler_class = HANDLERS_BY_NAME.get(name)
+        default_scopes = (
+            getattr(handler_class, "DEFAULT_SCOPES", []) if handler_class else []
+        )
+
+        # Check if provider has specific auth types from SDK registration
+        sdk_provider = AutoRegistry.get_provider(name)
+        if sdk_provider and sdk_provider.supported_auth_types:
+            supports_api_key = "api_key" in sdk_provider.supported_auth_types
+            supports_user_password = (
+                "user_password" in sdk_provider.supported_auth_types
+            )
+            supports_host_scoped = "host_scoped" in sdk_provider.supported_auth_types
+        else:
+            # Fallback for legacy providers
+            supports_api_key = True  # All providers can accept API keys
+            supports_user_password = name in ("smtp",)
+            supports_host_scoped = name == "http"
+
+        providers.append(
+            ProviderInfo(
+                name=name,
+                supports_oauth=supports_oauth,
+                supports_api_key=supports_api_key,
+                supports_user_password=supports_user_password,
+                supports_host_scoped=supports_host_scoped,
+                default_scopes=default_scopes,
+            )
+        )
+
+    return providers
+
+
+@integrations_router.post(
+    "/{provider}/oauth/initiate",
+    response_model=OAuthInitiateResponse,
+    summary="Initiate OAuth flow",
+)
+async def initiate_oauth(
+    provider: Annotated[str, Path(title="The OAuth provider")],
+    request: OAuthInitiateRequest,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
+    ),
+) -> OAuthInitiateResponse:
+    """
+    Initiate an OAuth flow for an external application.
+
+    This endpoint allows external apps to start an OAuth flow with a custom
+    callback URL. The callback URL must be from an allowed origin configured
+    in the platform settings.
+
+    Returns a login URL to redirect the user to, along with a state token
+    for CSRF protection.
+    """
+    # Validate callback URL
+    if not validate_callback_url(request.callback_url):
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=(
+                f"Callback URL origin is not allowed. "
+                f"Allowed origins: {settings.config.external_oauth_callback_origins}",
+            ),
+        )
+
+    # Validate provider
+    try:
+        provider_name = ProviderName(provider)
+    except ValueError:
+        # Check if it's a dynamically registered provider
+        if provider not in HANDLERS_BY_NAME:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Provider '{provider}' not found",
+            )
+        provider_name = provider
+
+    # Get OAuth handler with external callback URL
+    handler = _get_oauth_handler_for_external(
+        provider if isinstance(provider_name, str) else provider_name.value,
+        request.callback_url,
+    )
+
+    # Store state token with external flow metadata
+    # Note: initiated_by_api_key_id is only available for API key auth, not OAuth
+    api_key_id = getattr(auth, "id", None) if auth.type == "api_key" else None
+    state_token, code_challenge = await creds_manager.store.store_state_token(
+        user_id=auth.user_id,
+        provider=provider if isinstance(provider_name, str) else provider_name.value,
+        scopes=request.scopes,
+        callback_url=request.callback_url,
+        state_metadata=request.state_metadata,
+        initiated_by_api_key_id=api_key_id,
+    )
+
+    # Build login URL
+    login_url = handler.get_login_url(
+        request.scopes, state_token, code_challenge=code_challenge
+    )
+
+    # Calculate expiration (10 minutes from now)
+    from datetime import datetime, timedelta, timezone
+
+    expires_at = int((datetime.now(timezone.utc) + timedelta(minutes=10)).timestamp())
+
+    return OAuthInitiateResponse(
+        login_url=login_url,
+        state_token=state_token,
+        expires_at=expires_at,
+    )
+
+
+@integrations_router.post(
+    "/{provider}/oauth/complete",
+    response_model=OAuthCompleteResponse,
+    summary="Complete OAuth flow",
+)
+async def complete_oauth(
+    provider: Annotated[str, Path(title="The OAuth provider")],
+    request: OAuthCompleteRequest,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
+    ),
+) -> OAuthCompleteResponse:
+    """
+    Complete an OAuth flow by exchanging the authorization code for tokens.
+
+    This endpoint should be called after the user has authorized the application
+    and been redirected back to the external app's callback URL with an
+    authorization code.
+    """
+    # Verify state token
+    valid_state = await creds_manager.store.verify_state_token(
+        auth.user_id, request.state_token, provider
+    )
+
+    if not valid_state:
+        logger.warning(f"Invalid or expired state token for provider {provider}")
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Invalid or expired state token",
+        )
+
+    # Verify this is an external flow (callback_url must be set)
+    if not valid_state.callback_url:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="State token was not created for external OAuth flow",
+        )
+
+    # Get OAuth handler with the original callback URL
+    handler = _get_oauth_handler_for_external(provider, valid_state.callback_url)
+
+    try:
+        scopes = valid_state.scopes
+        scopes = handler.handle_default_scopes(scopes)
+
+        credentials = await handler.exchange_code_for_tokens(
+            request.code, scopes, valid_state.code_verifier
+        )
+
+        # Handle Linear's space-separated scopes
+        if len(credentials.scopes) == 1 and " " in credentials.scopes[0]:
+            credentials.scopes = credentials.scopes[0].split(" ")
+
+        # Check scope mismatch
+        if not set(scopes).issubset(set(credentials.scopes)):
+            logger.warning(
+                f"Granted scopes {credentials.scopes} for provider {provider} "
+                f"do not include all requested scopes {scopes}"
+            )
+
+    except Exception as e:
+        logger.error(f"OAuth2 Code->Token exchange failed for provider {provider}: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=f"OAuth2 callback failed to exchange code for tokens: {str(e)}",
+        )
+
+    # Store credentials
+    await creds_manager.create(auth.user_id, credentials)
+
+    logger.info(f"Successfully completed external OAuth for provider {provider}")
+
+    return OAuthCompleteResponse(
+        credentials_id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        state_metadata=valid_state.state_metadata,
+    )
+
+
+@integrations_router.get("/credentials", response_model=list[CredentialSummary])
+async def list_credentials(
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.READ_INTEGRATIONS)
+    ),
+) -> list[CredentialSummary]:
+    """
+    List all credentials for the authenticated user.
+
+    Returns metadata about each credential without exposing sensitive tokens.
+    """
+    credentials = await creds_manager.store.get_all_creds(auth.user_id)
+    return [
+        CredentialSummary(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+        )
+        for cred in credentials
+    ]
+
+
+@integrations_router.get(
+    "/{provider}/credentials", response_model=list[CredentialSummary]
+)
+async def list_credentials_by_provider(
+    provider: Annotated[str, Path(title="The provider to list credentials for")],
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.READ_INTEGRATIONS)
+    ),
+) -> list[CredentialSummary]:
+    """
+    List credentials for a specific provider.
+    """
+    credentials = await creds_manager.store.get_creds_by_provider(
+        auth.user_id, provider
+    )
+    return [
+        CredentialSummary(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+        )
+        for cred in credentials
+    ]
+
+
+@integrations_router.post(
+    "/{provider}/credentials",
+    response_model=CreateCredentialResponse,
+    status_code=status.HTTP_201_CREATED,
+    summary="Create credentials",
+)
+async def create_credential(
+    provider: Annotated[str, Path(title="The provider to create credentials for")],
+    request: Union[
+        CreateAPIKeyCredentialRequest,
+        CreateUserPasswordCredentialRequest,
+        CreateHostScopedCredentialRequest,
+    ] = Body(..., discriminator="type"),
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.MANAGE_INTEGRATIONS)
+    ),
+) -> CreateCredentialResponse:
+    """
+    Create non-OAuth credentials for a provider.
+
+    Supports creating:
+    - API key credentials (type: "api_key")
+    - Username/password credentials (type: "user_password")
+    - Host-scoped credentials (type: "host_scoped")
+
+    For OAuth credentials, use the OAuth initiate/complete flow instead.
+    """
+    # Validate provider exists
+    all_providers = get_all_provider_names()
+    if provider not in all_providers:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Provider '{provider}' not found",
+        )
+
+    # Create the appropriate credential type
+    credentials: Credentials
+    if request.type == "api_key":
+        credentials = APIKeyCredentials(
+            provider=provider,
+            api_key=SecretStr(request.api_key),
+            title=request.title,
+            expires_at=request.expires_at,
+        )
+    elif request.type == "user_password":
+        credentials = UserPasswordCredentials(
+            provider=provider,
+            username=SecretStr(request.username),
+            password=SecretStr(request.password),
+            title=request.title,
+        )
+    elif request.type == "host_scoped":
+        # Convert string headers to SecretStr
+        secret_headers = {k: SecretStr(v) for k, v in request.headers.items()}
+        credentials = HostScopedCredentials(
+            provider=provider,
+            host=request.host,
+            headers=secret_headers,
+            title=request.title,
+        )
+    else:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=f"Unsupported credential type: {request.type}",
+        )
+
+    # Store credentials
+    try:
+        await creds_manager.create(auth.user_id, credentials)
+    except Exception as e:
+        logger.error(f"Failed to store credentials: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"Failed to store credentials: {str(e)}",
+        )
+
+    logger.info(f"Created {request.type} credentials for provider {provider}")
+
+    return CreateCredentialResponse(
+        id=credentials.id,
+        provider=provider,
+        type=credentials.type,
+        title=credentials.title,
+    )
+
+
+class DeleteCredentialResponse(BaseModel):
+    """Response model for deleting a credential."""
+
+    deleted: bool = Field(..., description="Whether the credential was deleted")
+    credentials_id: str = Field(..., description="ID of the deleted credential")
+
+
+@integrations_router.delete(
+    "/{provider}/credentials/{cred_id}",
+    response_model=DeleteCredentialResponse,
+)
+async def delete_credential(
+    provider: Annotated[str, Path(title="The provider")],
+    cred_id: Annotated[str, Path(title="The credential ID to delete")],
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.DELETE_INTEGRATIONS)
+    ),
+) -> DeleteCredentialResponse:
+    """
+    Delete a credential.
+
+    Note: This does not revoke the tokens with the provider. For full cleanup,
+    use the main API's delete endpoint which handles webhook cleanup and
+    token revocation.
+    """
+    creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
+    if not creds:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
+        )
+    if creds.provider != provider:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Credentials do not match the specified provider",
+        )
+
+    await creds_manager.delete(auth.user_id, cred_id)
+
+    return DeleteCredentialResponse(deleted=True, credentials_id=cred_id)

autogpt_platform/backend/backend/api/external/v1/routes.py

@@ -0,0 +1,328 @@
+import logging
+import urllib.parse
+from collections import defaultdict
+from typing import Annotated, Any, Literal, Optional, Sequence
+
+from fastapi import APIRouter, Body, HTTPException, Security
+from prisma.enums import AgentExecutionStatus, APIKeyPermission
+from pydantic import BaseModel, Field
+from typing_extensions import TypedDict
+
+import backend.api.features.store.cache as store_cache
+import backend.api.features.store.model as store_model
+import backend.data.block
+from backend.api.external.middleware import require_permission
+from backend.data import execution as execution_db
+from backend.data import graph as graph_db
+from backend.data import user as user_db
+from backend.data.auth.base import APIAuthorizationInfo
+from backend.data.block import BlockInput, CompletedBlockOutput
+from backend.executor.utils import add_graph_execution
+from backend.util.settings import Settings
+
+from .integrations import integrations_router
+from .tools import tools_router
+
+settings = Settings()
+logger = logging.getLogger(__name__)
+
+v1_router = APIRouter()
+
+v1_router.include_router(integrations_router)
+v1_router.include_router(tools_router)
+
+
+class UserInfoResponse(BaseModel):
+    id: str
+    name: Optional[str]
+    email: str
+    timezone: str = Field(
+        description="The user's last known timezone (e.g. 'Europe/Amsterdam'), "
+        "or 'not-set' if not set"
+    )
+
+
+@v1_router.get(
+    path="/me",
+    tags=["user", "meta"],
+)
+async def get_user_info(
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.IDENTITY)
+    ),
+) -> UserInfoResponse:
+    user = await user_db.get_user_by_id(auth.user_id)
+
+    return UserInfoResponse(
+        id=user.id,
+        name=user.name,
+        email=user.email,
+        timezone=user.timezone,
+    )
+
+
+@v1_router.get(
+    path="/blocks",
+    tags=["blocks"],
+    dependencies=[Security(require_permission(APIKeyPermission.READ_BLOCK))],
+)
+async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
+    blocks = [block() for block in backend.data.block.get_blocks().values()]
+    return [b.to_dict() for b in blocks if not b.disabled]
+
+
+@v1_router.post(
+    path="/blocks/{block_id}/execute",
+    tags=["blocks"],
+    dependencies=[Security(require_permission(APIKeyPermission.EXECUTE_BLOCK))],
+)
+async def execute_graph_block(
+    block_id: str,
+    data: BlockInput,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.EXECUTE_BLOCK)
+    ),
+) -> CompletedBlockOutput:
+    obj = backend.data.block.get_block(block_id)
+    if not obj:
+        raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
+
+    output = defaultdict(list)
+    async for name, data in obj.execute(data):
+        output[name].append(data)
+    return output
+
+
+@v1_router.post(
+    path="/graphs/{graph_id}/execute/{graph_version}",
+    tags=["graphs"],
+)
+async def execute_graph(
+    graph_id: str,
+    graph_version: int,
+    node_input: Annotated[dict[str, Any], Body(..., embed=True, default_factory=dict)],
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.EXECUTE_GRAPH)
+    ),
+) -> dict[str, Any]:
+    try:
+        graph_exec = await add_graph_execution(
+            graph_id=graph_id,
+            user_id=auth.user_id,
+            inputs=node_input,
+            graph_version=graph_version,
+        )
+        return {"id": graph_exec.id}
+    except Exception as e:
+        msg = str(e).encode().decode("unicode_escape")
+        raise HTTPException(status_code=400, detail=msg)
+
+
+class ExecutionNode(TypedDict):
+    node_id: str
+    input: Any
+    output: dict[str, Any]
+
+
+class GraphExecutionResult(TypedDict):
+    execution_id: str
+    status: str
+    nodes: list[ExecutionNode]
+    output: Optional[list[dict[str, str]]]
+
+
+@v1_router.get(
+    path="/graphs/{graph_id}/executions/{graph_exec_id}/results",
+    tags=["graphs"],
+)
+async def get_graph_execution_results(
+    graph_id: str,
+    graph_exec_id: str,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.READ_GRAPH)
+    ),
+) -> GraphExecutionResult:
+    graph_exec = await execution_db.get_graph_execution(
+        user_id=auth.user_id,
+        execution_id=graph_exec_id,
+        include_node_executions=True,
+    )
+    if not graph_exec:
+        raise HTTPException(
+            status_code=404, detail=f"Graph execution #{graph_exec_id} not found."
+        )
+
+    if not await graph_db.get_graph(
+        graph_id=graph_exec.graph_id,
+        version=graph_exec.graph_version,
+        user_id=auth.user_id,
+    ):
+        raise HTTPException(status_code=404, detail=f"Graph #{graph_id} not found.")
+
+    return GraphExecutionResult(
+        execution_id=graph_exec_id,
+        status=graph_exec.status.value,
+        nodes=[
+            ExecutionNode(
+                node_id=node_exec.node_id,
+                input=node_exec.input_data.get("value", node_exec.input_data),
+                output={k: v for k, v in node_exec.output_data.items()},
+            )
+            for node_exec in graph_exec.node_executions
+        ],
+        output=(
+            [
+                {name: value}
+                for name, values in graph_exec.outputs.items()
+                for value in values
+            ]
+            if graph_exec.status == AgentExecutionStatus.COMPLETED
+            else None
+        ),
+    )
+
+
+##############################################
+############### Store Endpoints ##############
+##############################################
+
+
+@v1_router.get(
+    path="/store/agents",
+    tags=["store"],
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    response_model=store_model.StoreAgentsResponse,
+)
+async def get_store_agents(
+    featured: bool = False,
+    creator: str | None = None,
+    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
+    search_query: str | None = None,
+    category: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> store_model.StoreAgentsResponse:
+    """
+    Get a paginated list of agents from the store with optional filtering and sorting.
+
+    Args:
+        featured: Filter to only show featured agents
+        creator: Filter agents by creator username
+        sorted_by: Sort agents by "runs", "rating", "name", or "updated_at"
+        search_query: Search agents by name, subheading and description
+        category: Filter agents by category
+        page: Page number for pagination (default 1)
+        page_size: Number of agents per page (default 20)
+
+    Returns:
+        StoreAgentsResponse: Paginated list of agents matching the filters
+    """
+    if page < 1:
+        raise HTTPException(status_code=422, detail="Page must be greater than 0")
+
+    if page_size < 1:
+        raise HTTPException(status_code=422, detail="Page size must be greater than 0")
+
+    agents = await store_cache._get_cached_store_agents(
+        featured=featured,
+        creator=creator,
+        sorted_by=sorted_by,
+        search_query=search_query,
+        category=category,
+        page=page,
+        page_size=page_size,
+    )
+    return agents
+
+
+@v1_router.get(
+    path="/store/agents/{username}/{agent_name}",
+    tags=["store"],
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    response_model=store_model.StoreAgentDetails,
+)
+async def get_store_agent(
+    username: str,
+    agent_name: str,
+) -> store_model.StoreAgentDetails:
+    """
+    Get details of a specific store agent by username and agent name.
+
+    Args:
+        username: Creator's username
+        agent_name: Name/slug of the agent
+
+    Returns:
+        StoreAgentDetails: Detailed information about the agent
+    """
+    username = urllib.parse.unquote(username).lower()
+    agent_name = urllib.parse.unquote(agent_name).lower()
+    agent = await store_cache._get_cached_agent_details(
+        username=username, agent_name=agent_name
+    )
+    return agent
+
+
+@v1_router.get(
+    path="/store/creators",
+    tags=["store"],
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    response_model=store_model.CreatorsResponse,
+)
+async def get_store_creators(
+    featured: bool = False,
+    search_query: str | None = None,
+    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> store_model.CreatorsResponse:
+    """
+    Get a paginated list of store creators with optional filtering and sorting.
+
+    Args:
+        featured: Filter to only show featured creators
+        search_query: Search creators by profile description
+        sorted_by: Sort by "agent_rating", "agent_runs", or "num_agents"
+        page: Page number for pagination (default 1)
+        page_size: Number of creators per page (default 20)
+
+    Returns:
+        CreatorsResponse: Paginated list of creators matching the filters
+    """
+    if page < 1:
+        raise HTTPException(status_code=422, detail="Page must be greater than 0")
+
+    if page_size < 1:
+        raise HTTPException(status_code=422, detail="Page size must be greater than 0")
+
+    creators = await store_cache._get_cached_store_creators(
+        featured=featured,
+        search_query=search_query,
+        sorted_by=sorted_by,
+        page=page,
+        page_size=page_size,
+    )
+    return creators
+
+
+@v1_router.get(
+    path="/store/creators/{username}",
+    tags=["store"],
+    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    response_model=store_model.CreatorDetails,
+)
+async def get_store_creator(
+    username: str,
+) -> store_model.CreatorDetails:
+    """
+    Get details of a specific store creator by username.
+
+    Args:
+        username: Creator's username
+
+    Returns:
+        CreatorDetails: Detailed information about the creator
+    """
+    username = urllib.parse.unquote(username).lower()
+    creator = await store_cache._get_cached_creator_details(username=username)
+    return creator

autogpt_platform/backend/backend/api/external/v1/tools.py

@@ -0,0 +1,152 @@
+"""External API routes for chat tools - stateless HTTP endpoints.
+
+Note: These endpoints use ephemeral sessions that are not persisted to Redis.
+As a result, session-based rate limiting (max_agent_runs, max_agent_schedules)
+is not enforced for external API calls. Each request creates a fresh session
+with zeroed counters. Rate limiting for external API consumers should be
+handled separately (e.g., via API key quotas).
+"""
+
+import logging
+from typing import Any
+
+from fastapi import APIRouter, Security
+from prisma.enums import APIKeyPermission
+from pydantic import BaseModel, Field
+
+from backend.api.external.middleware import require_permission
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
+from backend.api.features.chat.tools.models import ToolResponseBase
+from backend.data.auth.base import APIAuthorizationInfo
+
+logger = logging.getLogger(__name__)
+
+tools_router = APIRouter(prefix="/tools", tags=["tools"])
+
+# Note: We use Security() as a function parameter dependency (auth: APIAuthorizationInfo = Security(...))
+# rather than in the decorator's dependencies= list. This avoids duplicate permission checks
+# while still enforcing auth AND giving us access to auth for extracting user_id.
+
+
+# Request models
+class FindAgentRequest(BaseModel):
+    query: str = Field(..., description="Search query for finding agents")
+
+
+class RunAgentRequest(BaseModel):
+    """Request to run or schedule an agent.
+
+    The tool automatically handles the setup flow:
+    - First call returns available inputs so user can decide what values to use
+    - Returns missing credentials if user needs to configure them
+    - Executes when inputs are provided OR use_defaults=true
+    - Schedules execution if schedule_name and cron are provided
+    """
+
+    username_agent_slug: str = Field(
+        ...,
+        description="The marketplace agent slug (e.g., 'username/agent-name')",
+    )
+    inputs: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Dictionary of input values for the agent",
+    )
+    use_defaults: bool = Field(
+        default=False,
+        description="Set to true to run with default values (user must confirm)",
+    )
+    schedule_name: str | None = Field(
+        None,
+        description="Name for scheduled execution (triggers scheduling mode)",
+    )
+    cron: str | None = Field(
+        None,
+        description="Cron expression (5 fields: minute hour day month weekday)",
+    )
+    timezone: str = Field(
+        default="UTC",
+        description="IANA timezone (e.g., 'America/New_York', 'UTC')",
+    )
+
+
+def _create_ephemeral_session(user_id: str) -> ChatSession:
+    """Create an ephemeral session for stateless API requests."""
+    return ChatSession.new(user_id)
+
+
+@tools_router.post(
+    path="/find-agent",
+)
+async def find_agent(
+    request: FindAgentRequest,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.USE_TOOLS)
+    ),
+) -> dict[str, Any]:
+    """
+    Search for agents in the marketplace based on capabilities and user needs.
+
+    Args:
+        request: Search query for finding agents
+
+    Returns:
+        List of matching agents or no results response
+    """
+    session = _create_ephemeral_session(auth.user_id)
+    result = await find_agent_tool._execute(
+        user_id=auth.user_id,
+        session=session,
+        query=request.query,
+    )
+    return _response_to_dict(result)
+
+
+@tools_router.post(
+    path="/run-agent",
+)
+async def run_agent(
+    request: RunAgentRequest,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.USE_TOOLS)
+    ),
+) -> dict[str, Any]:
+    """
+    Run or schedule an agent from the marketplace.
+
+    The endpoint automatically handles the setup flow:
+    - Returns missing inputs if required fields are not provided
+    - Returns missing credentials if user needs to configure them
+    - Executes immediately if all requirements are met
+    - Schedules execution if schedule_name and cron are provided
+
+    For scheduled execution:
+    - Cron format: "minute hour day month weekday"
+    - Examples: "0 9 * * 1-5" (9am weekdays), "0 0 * * *" (daily at midnight)
+    - Timezone: Use IANA timezone names like "America/New_York"
+
+    Args:
+        request: Agent slug, inputs, and optional schedule config
+
+    Returns:
+        - setup_requirements: If inputs or credentials are missing
+        - execution_started: If agent was run or scheduled successfully
+        - error: If something went wrong
+    """
+    session = _create_ephemeral_session(auth.user_id)
+    result = await run_agent_tool._execute(
+        user_id=auth.user_id,
+        session=session,
+        username_agent_slug=request.username_agent_slug,
+        inputs=request.inputs,
+        use_defaults=request.use_defaults,
+        schedule_name=request.schedule_name or "",
+        cron=request.cron or "",
+        timezone=request.timezone,
+    )
+    return _response_to_dict(result)
+
+
+def _response_to_dict(result: ToolResponseBase) -> dict[str, Any]:
+    """Convert a tool response to a dictionary for JSON serialization."""
+    return result.model_dump()

autogpt_platform/backend/backend/api/features/admin/credit_admin_routes.py

@@ -6,9 +6,10 @@ from fastapi import APIRouter, Body, Security
 from prisma.enums import CreditTransactionType
 
 from backend.data.credit import admin_get_user_history, get_user_credit_model
-from backend.server.v2.admin.model import AddUserCreditsResponse, UserHistoryResponse
 from backend.util.json import SafeJson
 
+from .model import AddUserCreditsResponse, UserHistoryResponse
+
 logger = logging.getLogger(__name__)
 
 

autogpt_platform/backend/backend/api/features/admin/credit_admin_routes_test.py

@@ -9,14 +9,15 @@ import pytest_mock
 from autogpt_libs.auth.jwt_utils import get_jwt_payload
 from pytest_snapshot.plugin import Snapshot
 
-import backend.server.v2.admin.credit_admin_routes as credit_admin_routes
-import backend.server.v2.admin.model as admin_model
 from backend.data.model import UserTransaction
 from backend.util.json import SafeJson
 from backend.util.models import Pagination
 
+from .credit_admin_routes import router as credit_admin_router
+from .model import UserHistoryResponse
+
 app = fastapi.FastAPI()
-app.include_router(credit_admin_routes.router)
+app.include_router(credit_admin_router)
 
 client = fastapi.testclient.TestClient(app)
 
@@ -30,7 +31,7 @@ def setup_app_admin_auth(mock_jwt_admin):
 
 
 def test_add_user_credits_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     configured_snapshot: Snapshot,
     admin_user_id: str,
     target_user_id: str,
@@ -42,7 +43,7 @@ def test_add_user_credits_success(
         return_value=(1500, "transaction-123-uuid")
     )
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
+        "backend.api.features.admin.credit_admin_routes.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -84,7 +85,7 @@ def test_add_user_credits_success(
 
 
 def test_add_user_credits_negative_amount(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test credit deduction by admin (negative amount)"""
@@ -94,7 +95,7 @@ def test_add_user_credits_negative_amount(
         return_value=(200, "transaction-456-uuid")
     )
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.get_user_credit_model",
+        "backend.api.features.admin.credit_admin_routes.get_user_credit_model",
         return_value=mock_credit_model,
     )
 
@@ -119,12 +120,12 @@ def test_add_user_credits_negative_amount(
 
 
 def test_get_user_history_success(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test successful retrieval of user credit history"""
     # Mock the admin_get_user_history function
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[
             UserTransaction(
                 user_id="user-1",
@@ -150,7 +151,7 @@ def test_get_user_history_success(
     )
 
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 
@@ -170,12 +171,12 @@ def test_get_user_history_success(
 
 
 def test_get_user_history_with_filters(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test user credit history with search and filter parameters"""
     # Mock the admin_get_user_history function
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[
             UserTransaction(
                 user_id="user-3",
@@ -194,7 +195,7 @@ def test_get_user_history_with_filters(
     )
 
     mock_get_history = mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 
@@ -230,12 +231,12 @@ def test_get_user_history_with_filters(
 
 
 def test_get_user_history_empty_results(
-    mocker: pytest_mock.MockFixture,
+    mocker: pytest_mock.MockerFixture,
     snapshot: Snapshot,
 ) -> None:
     """Test user credit history with no results"""
     # Mock empty history response
-    mock_history_response = admin_model.UserHistoryResponse(
+    mock_history_response = UserHistoryResponse(
         history=[],
         pagination=Pagination(
             total_items=0,
@@ -246,7 +247,7 @@ def test_get_user_history_empty_results(
     )
 
     mocker.patch(
-        "backend.server.v2.admin.credit_admin_routes.admin_get_user_history",
+        "backend.api.features.admin.credit_admin_routes.admin_get_user_history",
         return_value=mock_history_response,
     )
 

autogpt_platform/backend/backend/api/features/admin/execution_analytics_routes.py

@@ -7,6 +7,11 @@ from autogpt_libs.auth import get_user_id, requires_admin_user
 from fastapi import APIRouter, HTTPException, Security
 from pydantic import BaseModel, Field
 
+from backend.blocks.llm import LlmModel
+from backend.data.analytics import (
+    AccuracyTrendsResponse,
+    get_accuracy_trends_and_alerts,
+)
 from backend.data.execution import (
     ExecutionStatus,
     GraphExecutionMeta,
@@ -15,6 +20,8 @@ from backend.data.execution import (
 )
 from backend.data.model import GraphExecutionStats
 from backend.executor.activity_status_generator import (
+    DEFAULT_SYSTEM_PROMPT,
+    DEFAULT_USER_PROMPT,
     generate_activity_status_for_execution,
 )
 from backend.executor.manager import get_db_async_client
@@ -30,12 +37,21 @@ class ExecutionAnalyticsRequest(BaseModel):
     created_after: Optional[datetime] = Field(
         None, description="Optional created date lower bound"
     )
-    model_name: Optional[str] = Field(
-        "gpt-4o-mini", description="Model to use for generation"
-    )
+    model_name: str = Field("gpt-4o-mini", description="Model to use for generation")
     batch_size: int = Field(
         10, description="Batch size for concurrent processing", le=25, ge=1
     )
+    system_prompt: Optional[str] = Field(
+        None, description="Custom system prompt (default: built-in prompt)"
+    )
+    user_prompt: Optional[str] = Field(
+        None,
+        description="Custom user prompt with {{GRAPH_NAME}} and {{EXECUTION_DATA}} placeholders (default: built-in prompt)",
+    )
+    skip_existing: bool = Field(
+        True,
+        description="Whether to skip executions that already have activity status and correctness score",
+    )
 
 
 class ExecutionAnalyticsResult(BaseModel):
@@ -58,6 +74,31 @@ class ExecutionAnalyticsResponse(BaseModel):
     results: list[ExecutionAnalyticsResult]
 
 
+class ModelInfo(BaseModel):
+    value: str
+    label: str
+    provider: str
+
+
+class ExecutionAnalyticsConfig(BaseModel):
+    available_models: list[ModelInfo]
+    default_system_prompt: str
+    default_user_prompt: str
+    recommended_model: str
+
+
+class AccuracyTrendsRequest(BaseModel):
+    graph_id: str = Field(..., description="Graph ID to analyze", min_length=1)
+    user_id: Optional[str] = Field(None, description="Optional user ID filter")
+    days_back: int = Field(30, description="Number of days to look back", ge=7, le=90)
+    drop_threshold: float = Field(
+        10.0, description="Alert threshold percentage", ge=1.0, le=50.0
+    )
+    include_historical: bool = Field(
+        False, description="Include historical data for charts"
+    )
+
+
 router = APIRouter(
     prefix="/admin",
     tags=["admin", "execution_analytics"],
@@ -65,6 +106,100 @@ router = APIRouter(
 )
 
 
+@router.get(
+    "/execution_analytics/config",
+    response_model=ExecutionAnalyticsConfig,
+    summary="Get Execution Analytics Configuration",
+)
+async def get_execution_analytics_config(
+    admin_user_id: str = Security(get_user_id),
+):
+    """
+    Get the configuration for execution analytics including:
+    - Available AI models with metadata
+    - Default system and user prompts
+    - Recommended model selection
+    """
+    logger.info(f"Admin user {admin_user_id} requesting execution analytics config")
+
+    # Generate model list from LlmModel enum with provider information
+    available_models = []
+
+    # Function to generate friendly display names from model values
+    def generate_model_label(model: LlmModel) -> str:
+        """Generate a user-friendly label from the model enum value."""
+        value = model.value
+
+        # For all models, convert underscores/hyphens to spaces and title case
+        # e.g., "gpt-4-turbo" -> "GPT 4 Turbo", "claude-3-haiku-20240307" -> "Claude 3 Haiku"
+        parts = value.replace("_", "-").split("-")
+
+        # Handle provider prefixes (e.g., "google/", "x-ai/")
+        if "/" in value:
+            _, model_name = value.split("/", 1)
+            parts = model_name.replace("_", "-").split("-")
+
+        # Capitalize and format parts
+        formatted_parts = []
+        for part in parts:
+            # Skip date-like patterns - check for various date formats:
+            # - Long dates like "20240307" (8 digits)
+            # - Year components like "2024", "2025" (4 digit years >= 2020)
+            # - Month/day components like "04", "16" when they appear to be dates
+            if part.isdigit():
+                if len(part) >= 8:  # Long date format like "20240307"
+                    continue
+                elif len(part) == 4 and int(part) >= 2020:  # Year like "2024", "2025"
+                    continue
+                elif len(part) <= 2 and int(part) <= 31:  # Month/day like "04", "16"
+                    # Skip if this looks like a date component (basic heuristic)
+                    continue
+            # Keep version numbers as-is
+            if part.replace(".", "").isdigit():
+                formatted_parts.append(part)
+            # Capitalize normal words
+            else:
+                formatted_parts.append(
+                    part.upper()
+                    if part.upper() in ["GPT", "LLM", "API", "V0"]
+                    else part.capitalize()
+                )
+
+        model_name = " ".join(formatted_parts)
+
+        # Format provider name for better display
+        provider_name = model.provider.replace("_", " ").title()
+
+        # Return with provider prefix for clarity
+        return f"{provider_name}: {model_name}"
+
+    # Include all LlmModel values (no more filtering by hardcoded list)
+    recommended_model = LlmModel.GPT4O_MINI.value
+    for model in LlmModel:
+        label = generate_model_label(model)
+        # Add "(Recommended)" suffix to the recommended model
+        if model.value == recommended_model:
+            label += " (Recommended)"
+
+        available_models.append(
+            ModelInfo(
+                value=model.value,
+                label=label,
+                provider=model.provider,
+            )
+        )
+
+    # Sort models by provider and name for better UX
+    available_models.sort(key=lambda x: (x.provider, x.label))
+
+    return ExecutionAnalyticsConfig(
+        available_models=available_models,
+        default_system_prompt=DEFAULT_SYSTEM_PROMPT,
+        default_user_prompt=DEFAULT_USER_PROMPT,
+        recommended_model=recommended_model,
+    )
+
+
 @router.post(
     "/execution_analytics",
     response_model=ExecutionAnalyticsResponse,
@@ -100,6 +235,7 @@ async def generate_execution_analytics(
         # Fetch executions to process
         executions = await get_graph_executions(
             graph_id=request.graph_id,
+            graph_version=request.graph_version,
             user_id=request.user_id,
             created_time_gte=request.created_after,
             statuses=[
@@ -113,21 +249,20 @@ async def generate_execution_analytics(
             f"Found {len(executions)} total executions for graph {request.graph_id}"
         )
 
-        # Filter executions that need analytics generation (missing activity_status or correctness_score)
+        # Filter executions that need analytics generation
         executions_to_process = []
         for execution in executions:
+            # Skip if we should skip existing analytics and both activity_status and correctness_score exist
             if (
-                not execution.stats
-                or not execution.stats.activity_status
-                or execution.stats.correctness_score is None
+                request.skip_existing
+                and execution.stats
+                and execution.stats.activity_status
+                and execution.stats.correctness_score is not None
             ):
+                continue
 
-                # If version is specified, filter by it
-                if (
-                    request.graph_version is None
-                    or execution.graph_version == request.graph_version
-                ):
-                    executions_to_process.append(execution)
+            # Add execution to processing list
+            executions_to_process.append(execution)
 
         logger.info(
             f"Found {len(executions_to_process)} executions needing analytics generation"
@@ -152,9 +287,7 @@ async def generate_execution_analytics(
                     f"Processing batch {batch_idx + 1}/{total_batches} with {len(batch)} executions"
                 )
 
-                batch_results = await _process_batch(
-                    batch, request.model_name or "gpt-4o-mini", db_client
-                )
+                batch_results = await _process_batch(batch, request, db_client)
 
                 for result in batch_results:
                     results.append(result)
@@ -212,7 +345,7 @@ async def generate_execution_analytics(
 
 
 async def _process_batch(
-    executions, model_name: str, db_client
+    executions, request: ExecutionAnalyticsRequest, db_client
 ) -> list[ExecutionAnalyticsResult]:
     """Process a batch of executions concurrently."""
 
@@ -237,8 +370,11 @@ async def _process_batch(
                 db_client=db_client,
                 user_id=execution.user_id,
                 execution_status=execution.status,
-                model_name=model_name,  # Pass model name parameter
+                model_name=request.model_name,
                 skip_feature_flag=True,  # Admin endpoint bypasses feature flags
+                system_prompt=request.system_prompt or DEFAULT_SYSTEM_PROMPT,
+                user_prompt=request.user_prompt or DEFAULT_USER_PROMPT,
+                skip_existing=request.skip_existing,
             )
 
             if not activity_response:
@@ -299,3 +435,40 @@ async def _process_batch(
     return await asyncio.gather(
         *[process_single_execution(execution) for execution in executions]
     )
+
+
+@router.get(
+    "/execution_accuracy_trends",
+    response_model=AccuracyTrendsResponse,
+    summary="Get Execution Accuracy Trends and Alerts",
+)
+async def get_execution_accuracy_trends(
+    graph_id: str,
+    user_id: Optional[str] = None,
+    days_back: int = 30,
+    drop_threshold: float = 10.0,
+    include_historical: bool = False,
+    admin_user_id: str = Security(get_user_id),
+) -> AccuracyTrendsResponse:
+    """
+    Get execution accuracy trends with moving averages and alert detection.
+    Simple single-query approach.
+    """
+    logger.info(
+        f"Admin user {admin_user_id} requesting accuracy trends for graph {graph_id}"
+    )
+
+    try:
+        result = await get_accuracy_trends_and_alerts(
+            graph_id=graph_id,
+            days_back=days_back,
+            user_id=user_id,
+            drop_threshold=drop_threshold,
+            include_historical=include_historical,
+        )
+
+        return result
+
+    except Exception as e:
+        logger.exception(f"Error getting accuracy trends for graph {graph_id}: {e}")
+        raise HTTPException(status_code=500, detail=str(e))

autogpt_platform/backend/backend/api/features/admin/store_admin_routes.py

@@ -7,9 +7,9 @@ import fastapi
 import fastapi.responses
 import prisma.enums
 
-import backend.server.v2.store.cache as store_cache
-import backend.server.v2.store.db
-import backend.server.v2.store.model
+import backend.api.features.store.cache as store_cache
+import backend.api.features.store.db as store_db
+import backend.api.features.store.model as store_model
 import backend.util.json
 
 logger = logging.getLogger(__name__)
@@ -24,7 +24,7 @@ router = fastapi.APIRouter(
 @router.get(
     "/listings",
     summary="Get Admin Listings History",
-    response_model=backend.server.v2.store.model.StoreListingsWithVersionsResponse,
+    response_model=store_model.StoreListingsWithVersionsResponse,
 )
 async def get_admin_listings_with_versions(
     status: typing.Optional[prisma.enums.SubmissionStatus] = None,
@@ -48,7 +48,7 @@ async def get_admin_listings_with_versions(
         StoreListingsWithVersionsResponse with listings and their versions
     """
     try:
-        listings = await backend.server.v2.store.db.get_admin_listings_with_versions(
+        listings = await store_db.get_admin_listings_with_versions(
             status=status,
             search_query=search,
             page=page,
@@ -68,11 +68,11 @@ async def get_admin_listings_with_versions(
 @router.post(
     "/submissions/{store_listing_version_id}/review",
     summary="Review Store Submission",
-    response_model=backend.server.v2.store.model.StoreSubmission,
+    response_model=store_model.StoreSubmission,
 )
 async def review_submission(
     store_listing_version_id: str,
-    request: backend.server.v2.store.model.ReviewSubmissionRequest,
+    request: store_model.ReviewSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
 ):
     """
@@ -87,12 +87,10 @@ async def review_submission(
         StoreSubmission with updated review information
     """
     try:
-        already_approved = (
-            await backend.server.v2.store.db.check_submission_already_approved(
-                store_listing_version_id=store_listing_version_id,
-            )
+        already_approved = await store_db.check_submission_already_approved(
+            store_listing_version_id=store_listing_version_id,
         )
-        submission = await backend.server.v2.store.db.review_store_submission(
+        submission = await store_db.review_store_submission(
             store_listing_version_id=store_listing_version_id,
             is_approved=request.is_approved,
             external_comments=request.comments,
@@ -136,7 +134,7 @@ async def admin_download_agent_file(
     Raises:
         HTTPException: If the agent is not found or an unexpected error occurs.
     """
-    graph_data = await backend.server.v2.store.db.get_agent_as_admin(
+    graph_data = await store_db.get_agent_as_admin(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
     )

autogpt_platform/backend/backend/api/features/analytics.py

@@ -6,10 +6,11 @@ from typing import Annotated
 import fastapi
 import pydantic
 from autogpt_libs.auth import get_user_id
+from autogpt_libs.auth.dependencies import requires_user
 
 import backend.data.analytics
 
-router = fastapi.APIRouter()
+router = fastapi.APIRouter(dependencies=[fastapi.Security(requires_user)])
 logger = logging.getLogger(__name__)