c1a1767034
- Add generate_block_docs.py script that introspects block code to
generate markdown
- Support manual content preservation via <!-- MANUAL: --> markers
- Add migrate_block_docs.py to preserve existing manual content from git
HEAD
- Add CI workflow (docs-block-sync.yml) to fail if docs drift from code
- Add Claude PR review workflow (docs-claude-review.yml) for doc changes
- Add manual LLM enhancement workflow (docs-enhance.yml)
- Add GitBook configuration (.gitbook.yaml, SUMMARY.md)
- Fix non-deterministic category ordering (categories is a set)
- Add comprehensive test suite (32 tests)
- Generate docs for 444 blocks with 66 preserved manual sections
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
<!-- Clearly explain the need for these changes: -->
### Changes 🏗️
<!-- Concisely describe all of the changes made in this pull request:
-->
### 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:
<!-- Put your test plan here: -->
- [x] Extensively test code generation for the docs pages
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Introduces an automated documentation pipeline for blocks and
integrates it into CI.
>
> - Adds `scripts/generate_block_docs.py` (+ tests) to introspect blocks
and generate `docs/integrations/**`, preserving `<!-- MANUAL: -->`
sections
> - New CI workflows: **docs-block-sync** (fails if docs drift),
**docs-claude-review** (AI review for block/docs PRs), and
**docs-enhance** (optional LLM improvements)
> - Updates existing Claude workflows to use `CLAUDE_CODE_OAUTH_TOKEN`
instead of `ANTHROPIC_API_KEY`
> - Improves numerous block descriptions/typos and links across backend
blocks to standardize docs output
> - Commits initial generated docs including
`docs/integrations/README.md` and many provider/category pages
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
631e53e0f6. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
3.1 KiB
System Store Operations
Blocks for browsing and retrieving agent details from the AutoGPT store.
Get Store Agent Details
What it is
Get detailed information about an agent from the store
How it works
This block retrieves detailed metadata about a specific agent from the AutoGPT store using the creator's username and agent slug. It returns the agent's name, description, categories, run count, and average rating.
The store_listing_version_id can be used with other blocks to add the agent to your library or execute it.
Inputs
| Input | Description | Type | Required |
|---|---|---|---|
| creator | The username of the agent creator | str | Yes |
| slug | The name of the agent | str | Yes |
Outputs
| Output | Description | Type |
|---|---|---|
| error | Error message if the operation failed | str |
| found | Whether the agent was found in the store | bool |
| store_listing_version_id | The store listing version ID | str |
| agent_name | Name of the agent | str |
| description | Description of the agent | str |
| creator | Creator of the agent | str |
| categories | Categories the agent belongs to | List[str] |
| runs | Number of times the agent has been run | int |
| rating | Average rating of the agent | float |
Possible use case
Agent Discovery: Fetch details about a specific agent before adding it to your library.
Agent Validation: Check an agent's ratings and run count to assess quality and popularity.
Dynamic Agent Selection: Get agent metadata to decide which version or variant to use.
Search Store Agents
What it is
Search for agents in the store
How it works
This block searches the AutoGPT agent store using a query string. Filter results by category and sort by rating, runs, or name. Limit controls the maximum number of results returned.
Results include basic agent information and are output both as a list and individually for workflow iteration.
Inputs
| Input | Description | Type | Required |
|---|---|---|---|
| query | Search query to find agents | str | No |
| category | Filter by category | str | No |
| sort_by | How to sort the results | "rating" | "runs" | "name" | "updated_at" | No |
| limit | Maximum number of results to return | int | No |
Outputs
| Output | Description | Type |
|---|---|---|
| error | Error message if the operation failed | str |
| agents | List of agents matching the search criteria | List[StoreAgent] |
| agent | Basic information of the agent | StoreAgent |
| total_count | Total number of agents found | int |
Possible use case
Agent Recommendation: Search for agents that match user needs and recommend the best options.
Marketplace Browse: Allow users to explore available agents by category or keyword.
Agent Orchestration: Find and compose multiple specialized agents for complex workflows.