project-logger
SQLite-based project documentation logger for tracking API references, components, and project progress. Use this skill when documenting code changes, adding API documentation, recording component updates, or tracking project milestones. Automatically invoked when user mentions documentation, changelog, API docs, component docs, or project updates.
Best use case
project-logger is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
SQLite-based project documentation logger for tracking API references, components, and project progress. Use this skill when documenting code changes, adding API documentation, recording component updates, or tracking project milestones. Automatically invoked when user mentions documentation, changelog, API docs, component docs, or project updates.
Teams using project-logger should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/project-logger/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How project-logger Compares
| Feature / Agent | project-logger | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
SQLite-based project documentation logger for tracking API references, components, and project progress. Use this skill when documenting code changes, adding API documentation, recording component updates, or tracking project milestones. Automatically invoked when user mentions documentation, changelog, API docs, component docs, or project updates.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 ```bash python ~/skills/project-logger/scripts/logger.py init ``` ### Add Documentation ```bash # 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 ```bash # 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 ```bash python ~/skills/project-logger/scripts/logger.py update api --id 1 --description "Updated description" ``` ### Export to Markdown (Optional) ```bash 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 documentation - `components` - React component documentation - `projects` - Project changelog and milestones - `doc_tags` - Tags for categorization - `doc_tag_relations` - Many-to-many tag relationships ## Additional Resources For detailed information, see: - [Database Schema](./schema.md) - Complete table definitions - [API Reference](./api-reference.md) - Full CLI command documentation - [Examples](./examples.md) - Usage examples and patterns - [Templates](./templates/) - Documentation templates ## Usage Patterns ### When Adding New Features 1. Add project entry with event "Added" 2. Add component entries for new UI components 3. Add API entries for new endpoints ### When Updating Existing Features 1. Add project entry with event "Updated" 2. Update component/API entries with new details ### When Removing Features 1. Add project entry with event "Removed" 2. Mark component/API entries as deprecated ## Integration with CI/CD The logger can be integrated into your CI/CD pipeline: ```yaml # ~/workflows/docs.yml - name: Generate docs run: python ~/skills/project-logger/scripts/logger.py export --format markdown ``` ## Best Practices 1. **Always timestamp entries** - The system auto-generates timestamps 2. **Use consistent naming** - Follow naming conventions for entries 3. **Add tags for searchability** - Tag entries for easier discovery 4. **Keep descriptions concise** - Detailed info goes in specific fields 5. **Link related entries** - Reference component IDs in API docs when relevant
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