project-logger
Documents API, components, and project progress using a structured SQLite database.
Install
mkdir -p .claude/skills/project-logger && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16037" && unzip -o skill.zip -d .claude/skills/project-logger && rm skill.zipInstalls to .claude/skills/project-logger
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Initialize a SQLite database for project documentation.
- →Add documentation entries for APIs, components, and projects.
- →Query documentation entries by type, ID, or search term.
- →Update existing documentation entries.
- →Export documentation to Markdown format.
- →Integrate documentation logging into CI/CD pipelines.
How it works
The skill uses a Python script to interact with a SQLite database, allowing programmatic management of API, component, and project documentation. It replaces traditional markdown files with a structured database.
Inputs & outputs
When to use project-logger
- →Logging API endpoints
- →Tracking component documentation
- →Recording project milestones
- →Updating project progress
About this skill
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
When not to use it
- →When traditional markdown-based documentation is preferred.
- →When the user needs to store documentation in a non-SQLite database.
Prerequisites
Limitations
- →It is based on SQLite, not other database types.
- →It replaces traditional markdown-based documentation.
- →It requires Python to run the logger scripts.
How it compares
This skill provides a programmatic, database-driven approach to project documentation, offering structured data and query capabilities, which is more organized than managing documentation solely through markdown files.
Compared to similar skills
project-logger side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| project-logger (this skill) | 0 | 5mo | Review | Beginner |
| database-documentation-gen | 2 | 1mo | Review | Intermediate |
| domain-model-documentation | 0 | 5mo | No flags | Intermediate |
| meta-authoring | 0 | 1mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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