multi-agent-ai-projects
Multi-Agent AI Projects
Guidelines for working with multi-agent AI learning projects and experimental codebases.
CRITICAL: First Actions When Starting or Resuming Work
Read STATUS.md FIRST (usually .spec/STATUS.md or project root) - Shows current phase, completed lessons, blockers, and resume instructions. This prevents working on wrong lessons or repeating completed work.
Then:
- Check git status
- Verify dependencies installed
- Check lesson-specific .env files
Auto-activate when: Project has .spec/ directory, lessons/ subdirectory, STATUS.md, or lesson-numbered directories.
Project Structure Recognition
More from ilude/claude-code-config
code-documentation
Guidelines for self-explanatory code and meaningful documentation. Activate when working with comments, docstrings, documentation, code clarity, API documentation, JSDoc, or discussing code commenting strategies. Guides on why over what, anti-patterns, decision frameworks, and language-specific examples.
12claude-code-workflow
Claude Code AI-assisted development workflow. Activate when discussing Claude Code usage, AI-assisted coding, prompting strategies, or Claude Code-specific patterns.
10css-workflow
CSS and styling workflow guidelines. Activate when working with CSS files (.css), Tailwind CSS, Stylelint, or styling-related tasks.
7api-design-patterns
Language-agnostic API design patterns covering REST and GraphQL, including resource naming, HTTP methods, status codes, versioning, pagination, filtering, authentication, error handling, and schema design. Activate when working with APIs, REST endpoints, GraphQL schemas, API documentation, OpenAPI/Swagger, JWT, OAuth2, endpoint design, API versioning, rate limiting, or GraphQL resolvers.
7container-workflow
Guidelines for containerized projects using Docker, Dockerfile, docker-compose, container, and containerization. Covers multi-stage builds, security, signal handling, entrypoint scripts, and deployment workflows.
6python-workflow
Python project workflow guidelines. Triggers: .py, pyproject.toml, uv, pip, pytest, Python. Covers package management, virtual environments, code style, type safety, testing, configuration, CQRS patterns, and Python-specific development tasks.
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