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This PR transforms GitHub Copilot from a general coding assistant into a platform-specific expert by providing comprehensive onboarding and a fully configured development environment that mirrors the AutoGPT platform's CI/CD pipeline. ## Key Features ### CI-Aligned Development Environment - **Production-Grade Setup**: The `copilot-setup-steps.yml` workflow now mirrors the platform's CI workflows, providing Copilot with the same environment used for testing and deployment - **Essential Services**: Automatically starts Docker services (PostgreSQL, Redis, RabbitMQ, ClamAV) required for platform development - **Database Readiness**: Includes Prisma migrations and client generation to ensure the database is immediately usable - **Environment Configuration**: Copies default environment files and validates service health, eliminating manual setup steps ### Comprehensive Platform Knowledge - **Unified Documentation**: The `copilot-instructions.md` file integrates knowledge from multiple sources (installer.md, advanced_setup.md, CLAUDE.md, AGENTS.md) into a single comprehensive guide - **Development Patterns**: Includes advanced patterns for block development, API creation, frontend work, and security implementation - **Architecture Insights**: Provides deep understanding of the agent block system, database schema, middleware, and CI/CD workflows - **Troubleshooting Guide**: Comprehensive error handling and validation steps based on production experience ### Enhanced Development Workflow ```bash # Before: Trial-and-error dependency installation # After: Fully configured environment ready immediately # Copilot now understands: poetry run serve # Backend server (port 8000) pnpm dev # Frontend server (port 3000) docker compose up -d # Essential services poetry run pytest backend/blocks/test/test_block.py -xvs # Block validation ``` ## Benefits This configuration provides Copilot with: - **Immediate Productivity**: No time wasted on environment setup or dependency discovery - **Platform Expertise**: Deep understanding of AutoGPT's architecture, security patterns, and development workflows - **CI Consistency**: Local development environment matches production testing environment - **Comprehensive Context**: Access to all platform documentation and development patterns in a single source The setup eliminates the slow trial-and-error process typical of LLM-based development tools and ensures Copilot works efficiently from the first interaction. ## References - [GitHub Copilot Agent Environment Setup](https://docs.github.com/en/copilot/how-tos/use-copilot-agents/coding-agent/customize-the-agent-environment#preinstalling-tools-or-dependencies-in-copilots-environment) - [AutoGPT Platform CI Workflows](.github/workflows/) - [Platform Development Guide](autogpt_platform/CLAUDE.md) <!-- START COPILOT CODING AGENT TIPS --> --- 💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more [Copilot coding agent tips](https://gh.io/copilot-coding-agent-tips) in the docs. --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: ntindle <8845353+ntindle@users.noreply.github.com> Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: Nicholas Tindle <nicktindle@outlook.com> Co-authored-by: Reinier van der Leer <pwuts@agpt.co>