- Add 15 comprehensive skills extracted from Windsurf workflows - Cover debugging, testing, releases, deployment, security, and documentation - Each skill includes step-by-step instructions and copy-pasteable commands - Skills organized by category with cross-references and difficulty levels
10 KiB
10 KiB
Update Agent Documentation Skill
Description: Scan all repos and regenerate AI assistant documentation (AGENTS.md, CLAUDE.md, etc.) across the workspace.
When to Use
- After adding new packages or services
- When changing coding conventions
- After architectural changes
- Periodically to keep docs current
- When onboarding new AI assistants
Repositories Covered
| Repo | Path | Scope |
|---|---|---|
| learning_voice_ai_agent | /Users/sd9235/code/mygh/learning_voice_ai_agent |
LysnrAI product code |
| learning_ai_common_plat | /Users/sd9235/code/mygh/learning_ai_common_plat |
Shared packages + services |
| learning_multimodal_memory_agents | /Users/sd9235/code/mygh/learning_multimodal_memory_agents |
MindLyst native app |
Files Updated Per Repo
| File | Tool | Format | Purpose |
|---|---|---|---|
AGENTS.md |
Universal | Detailed markdown | Full onboarding guide |
CLAUDE.md |
Claude Code | Compact markdown (<50 lines) | Quick reference |
.cursorrules |
Cursor AI | Plain text | Inline completion + chat rules |
.github/copilot-instructions.md |
GitHub Copilot | Markdown | Code generation rules |
.windsurfrules |
Windsurf/Codeium | Plain text | Project rules for memory |
.clinerules |
Cline/Roo Code | Plain text | Mandatory rules + file locations |
.aider.conf.yml |
Aider | YAML | Context files, conventions |
.editorconfig |
All editors | INI | Indent, charset, line ending |
Phase 1: Gather Current State
1. Scan learning_voice_ai_agent
cd /Users/sd9235/code/mygh/learning_voice_ai_agent
# Find all JS projects
find . -maxdepth 2 -type f -name "package.json" -not -path "*/node_modules/*" | head -20
# Find Python config
find . -maxdepth 1 -type f -name "*.py" -o -name "*.toml" -o -name "Makefile" | head -20
# Read key files
cat AGENTS.md
cat README_MONO_REPO.md
cat docker-compose.yml
cat pyproject.toml
# Check dashboard dependencies
find admin-dashboard-web user-dashboard-web tracker-dashboard-web -name "package.json" -exec grep "@bytelyst" {} \;
# List lib files
ls admin-dashboard-web/src/lib/
ls user-dashboard-web/src/lib/
ls tracker-dashboard-web/src/lib/
# Count tests
find tests/ -name "test_*.py" | wc -l
find admin-dashboard-web/src/app/api -name "route.ts" | wc -l
# Check CI workflows
ls -la .github/workflows/
# Check service topology
head -20 run-local-all-services.sh
2. Scan learning_ai_common_plat
cd /Users/sd9235/code/mygh/learning_ai_common_plat
# List all packages
find packages -maxdepth 2 -name "package.json" -not -path "*/node_modules/*"
# List all services
find services -maxdepth 2 -name "package.json" -not -path "*/node_modules/*"
# Read key files
cat AGENTS.md
cat README.md
cat pnpm-workspace.yaml
cat tsconfig.base.json
# Check package exports
find packages -name "src/index.ts" -exec echo "=== {} ===" \; -exec cat {} \;
# Check service modules
find services -name "src/server.ts" -exec echo "=== {} ===" \; -exec cat {} \;
# Count tests (quick)
pnpm test 2>&1 | tail -5
# Check design tokens
cat packages/design-tokens/tokens/bytelyst.tokens.json
ls packages/design-tokens/generated/
3. Scan learning_multimodal_memory_agents
cd /Users/sd9235/code/mygh/learning_multimodal_memory_agents
# Find source files
find mindlyst-native -maxdepth 3 -name "*.kt" -o -name "*.swift" -o -name "*.tsx" | head -30
# Read key files
cat AGENTS.md
cat README.md
cat ARCHITECTURE.md
# Check dependencies
cat mindlyst-native/gradle/libs.versions.toml
cat mindlyst-native/shared/build.gradle.kts
# List shared logic
ls mindlyst-native/shared/src/commonMain/kotlin/com/mindlyst/shared/
# List platform code
ls mindlyst-native/iosApp/
ls mindlyst-native/web/src/pages/
# Check token sync
head -20 design-system/web/mindlyst.css
Phase 2: Identify Changes
Compare gathered info against existing docs:
- New packages or services?
- Changed conventions?
- New file ownership patterns?
- Updated environment variables?
- Different test counts?
- New CI workflows?
Build a change summary before editing.
Phase 3: Update Documentation
1. Update AGENTS.md (Most Comprehensive)
Ensure these sections are current:
## Project Identity
- Product name, IDs, prefixes
- License format
- Config directory
## Monorepo Layout
- Directory tree with descriptions
- Include sibling repo structure
- Service ports and responsibilities
## Tech Stack Rules
- Python: version, linter, formatter, tests, logging
- TypeScript services: framework, patterns, database
- TypeScript dashboards: framework, shared packages
## Coding Conventions
- MUST follow rules
- MUST NOT do rules
- Commit message format
## File Ownership Map
- Table mapping domains → services → key files
- Include all @bytelyst/\* mappings
## How to Run Things
- Start services command
- Test commands
- Docker compose
- Seed database
## Common Patterns
- Adding Fastify modules
- Adding dashboard pages
- Adding service clients
- Adding backend routes
- Debugging methodology
## Environment Variables
- Required vars per service
- Env file locations
- Azure service references
## Key Documents
- "When you need to..." → "read this" table
2. Update CLAUDE.md (Compact Summary)
Keep under 50 lines:
- Identity (product, tech stack)
- Key commands (start services, run tests)
- Critical rules (MUST follow)
- Current @bytelyst/* wiring state
3. Update .cursorrules
Project: LysnrAI - Voice-to-text platform
Stack: Python 3.12 + FastAPI + Next.js 16 + Fastify 5
Rules:
- Always use req.log, never console.log
- Every Cosmos doc needs productId field
- Use @bytelyst/* packages from common_plat
- Commit: feat(scope): description
- See AGENTS.md for full details
4. Update .github/copilot-instructions.md
# LysnrAI Copilot Instructions
## Always Do
- Use structlog for Python logging
- Validate with Zod schemas in TypeScript
- Include productId in all Cosmos documents
- Use @bytelyst/api-client for service calls
## Never Do
- Use console.log in production
- Hardcode secrets or API keys
- Modify tests to make them pass
- Use any type in TypeScript
## Key Patterns
- Fastify modules: types.ts → repository.ts → routes.ts
- Dashboard pages: src/app/(dashboard)/page-name/page.tsx
- Python routes: backend/src/routes/name.py
See AGENTS.md for comprehensive guide.
5. Update .windsurfrules
Project: LysnrAI
Product ID: lysnrrai
Config dir: ~/.lysnrai/
Key services: backend(8000), billing(4002), growth(4001), platform(4003), tracker(4004)
Dashboards: admin(3001), user(3002), tracker(3003)
Rules: Use @bytelyst/* packages, no console.log, productId required, commit format: type(scope): desc
6. Update .clinerules
# LysnrAI Project Rules
- All business logic in backend/src/ or services/
- Dashboards in admin-dashboard-web/, user-dashboard-web/, tracker-dashboard-web/
- Shared packages in ../learning_ai_common_plat/packages/
- Use @bytelyst/cosmos for DB, @bytelyst/auth for JWT
- Python: use ruff lint, pytest tests
- TypeScript: use ESLint, Vitest tests
- Never commit .env files or secrets
7. Update .aider.conf.yml
# Aider configuration for LysnrAI
auto-commits: false
lint-cmd: |
python: ruff check --fix
typescript: pnpm lint
shell: shellcheck -f gcc
test-cmd: |
python: pytest tests/ -v
typescript: pnpm test
# Always include these files in context
context-files:
- AGENTS.md
- README_MONO_REPO.md
- docker-compose.yml
- pyproject.toml
- pnpm-workspace.yaml
- tsconfig.base.json
8. Update .editorconfig
# EditorConfig for LysnrAI
root = true
[*.py]
indent_style = space
indent_size = 4
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
[*.{js,ts,tsx,json}]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
[*.{kt,swift}]
indent_style = space
indent_size = 4
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
Phase 4: Validate Updates
# For each repo:
git add .
git commit -m "docs: update AI agent documentation"
git push
# Verify files are readable
cat AGENTS.md | head -20
cat CLAUDE.md
cat .cursorrules
Automation Script
Create scripts/update-all-agent-docs.sh:
#!/bin/bash
# Update all agent docs across repos
REPOS=(
"/Users/sd9235/code/mygh/learning_voice_ai_agent"
"/Users/sd9235/code/mygh/learning_ai_common_plat"
"/Users/sd9235/code/mygh/learning_multimodal_memory_agents"
)
for repo in "${REPOS[@]}"; do
echo "Updating docs in $repo"
cd "$repo"
# Run the update workflow
# (This would be the full workflow implementation)
git add .
git commit -m "docs: update AI agent documentation"
git push
done
Notes
- Be consistent - Keep the same structure across all repos
- Be specific - Include actual file paths and commands
- Stay current - Run this workflow regularly
- Get feedback - Ask developers if docs are helpful
- Version control - Track changes to understand evolution
Related Skills
- Production Readiness - Docs are part of readiness
- Local Development Setup - Docs should match local setup
- Debug Service - Docs should help with debugging