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project-logger

by diegosouzapwSource

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, change

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.zip

Installs 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.
350 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)

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:

TypeDescriptionTable
APIHTTP endpoints, request/response formats, status codesapi_docs
ComponentReact components, props, events, usage examplescomponents
ProjectMilestones, changes, progress trackingprojects

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 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:

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:

# ~/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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