Project Logger Skill
A SQLite-based documentation system for managing project documentation through Agent interactions. This replaces traditional markdown-based documentation with a structured database approach.
Overview
This skill provides a programmatic way to manage three types of documentation:
| Type | Description | Table |
|---|---|---|
| API | HTTP endpoints, request/response formats, status codes | api_docs |
| Component | React components, props, events, usage examples | components |
| Project | Milestones, changes, progress tracking | projects |
Quick Start
Initialize Database
python ~/skills/project-logger/scripts/logger.py init
Add Documentation
# Add API documentation
python ~/skills/project-logger/scripts/logger.py add api --name "Chat API" --path "/api/chat" --method "POST" --description "AI chat endpoint"
# Add Component documentation
python ~/skills/project-logger/scripts/logger.py add component --name "ChatPanel" --description "Main chat interface component"
# Add Project milestone
python ~/skills/project-logger/scripts/logger.py add project --title "v1.0 Release" --event "Added" --description "Initial release"
Query Documentation
# List all entries
python ~/skills/project-logger/scripts/logger.py list api
python ~/skills/project-logger/scripts/logger.py list component
python ~/skills/project-logger/scripts/logger.py list project
# Search entries
python ~/skills/project-logger/scripts/logger.py search "chat"
# Get specific entry
python ~/skills/project-logger/scripts/logger.py get api --id 1
Update Documentation
python ~/skills/project-logger/scripts/logger.py update api --id 1 --description "Updated description"
Export to Markdown (Optional)
python ~/skills/project-logger/scripts/logger.py export --format markdown --output ./docs/
Database Schema
The SQLite database is stored at ~/skills/project-logger/data/project_docs.db
Tables
api_docs- API endpoint documentationcomponents- React component documentationprojects- Project changelog and milestonesdoc_tags- Tags for categorizationdoc_tag_relations- Many-to-many tag relationships
Additional Resources
For detailed information, see:
- Database Schema - Complete table definitions
- API Reference - Full CLI command documentation
- Examples - Usage examples and patterns
- Templates - Documentation templates
Usage Patterns
When Adding New Features
- Add project entry with event "Added"
- Add component entries for new UI components
- Add API entries for new endpoints
When Updating Existing Features
- Add project entry with event "Updated"
- Update component/API entries with new details
When Removing Features
- Add project entry with event "Removed"
- Mark component/API entries as deprecated
Integration with CI/CD
The logger can be integrated into your CI/CD pipeline:
# ~/workflows/docs.yml
- name: Generate docs
run: python ~/skills/project-logger/scripts/logger.py export --format markdown
Best Practices
- Always timestamp entries - The system auto-generates timestamps
- Use consistent naming - Follow naming conventions for entries
- Add tags for searchability - Tag entries for easier discovery
- Keep descriptions concise - Detailed info goes in specific fields
- Link related entries - Reference component IDs in API docs when relevant