# Project Logger

> Project Logger Skill

- Skill: `aibot88/project-logger` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add aibot88/project-logger`
- Raw SKILL.md: https://api.skillmd.com/api/skills/aibot88/project-logger/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: aibot88 (https://skillmd.com/u/aibot88)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/aibot88/project-logger

---


# 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