- Comprehensive guide for AI assistants working with the codebase - Covers project structure, development commands, architecture patterns - Includes testing guidelines, CI/CD info, and troubleshooting - Documents all entry points, dependencies, and best practices
470 lines
12 KiB
Markdown
470 lines
12 KiB
Markdown
# AGENTS.md - Skill Seekers
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This file provides essential guidance for AI coding agents working with the Skill Seekers codebase.
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---
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## Project Overview
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**Skill Seekers** is a Python CLI tool that converts documentation websites, GitHub repositories, and PDF files into AI-ready skills for LLM platforms. It supports 4 target platforms:
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- **Claude AI** (ZIP + YAML format)
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- **Google Gemini** (tar.gz format)
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- **OpenAI ChatGPT** (ZIP + Vector Store)
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- **Generic Markdown** (universal ZIP export)
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**Current Version:** 2.7.4
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**Python Version:** 3.10+ required
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**License:** MIT
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**Website:** https://skillseekersweb.com/
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### Core Workflow
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1. **Scrape Phase** - Crawl documentation/GitHub/PDF sources
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2. **Build Phase** - Organize content into categorized references
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3. **Enhancement Phase** - AI-powered quality improvements (optional)
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4. **Package Phase** - Create platform-specific packages
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5. **Upload Phase** - Auto-upload to target platform (optional)
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---
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## Project Structure
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```
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/mnt/1ece809a-2821-4f10-aecb-fcdf34760c0b/Git/Skill_Seekers/
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├── src/skill_seekers/ # Main source code (src/ layout)
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│ ├── cli/ # CLI tools and commands
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│ │ ├── adaptors/ # Platform adaptors (Strategy pattern)
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│ │ │ ├── base.py # Abstract base class
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│ │ │ ├── claude.py # Claude AI adaptor
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│ │ │ ├── gemini.py # Google Gemini adaptor
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│ │ │ ├── openai.py # OpenAI ChatGPT adaptor
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│ │ │ └── markdown.py # Generic Markdown adaptor
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│ │ ├── main.py # Unified CLI entry point
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│ │ ├── doc_scraper.py # Documentation scraper
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│ │ ├── github_scraper.py # GitHub repository scraper
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│ │ ├── pdf_scraper.py # PDF extraction
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│ │ ├── unified_scraper.py # Multi-source scraping
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│ │ ├── codebase_scraper.py # Local codebase analysis (C2.x/C3.x)
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│ │ ├── enhance_skill_local.py # AI enhancement (LOCAL mode)
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│ │ ├── package_skill.py # Skill packager
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│ │ ├── upload_skill.py # Upload to platforms
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│ │ └── ... # 50+ CLI modules
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│ └── mcp/ # MCP server integration
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│ ├── server_fastmcp.py # FastMCP server (main)
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│ ├── server.py # Legacy server
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│ └── tools/ # MCP tool implementations
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├── tests/ # Test suite (76 test files)
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├── configs/ # Preset configuration files
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├── docs/ # Documentation (54 markdown files)
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├── .github/workflows/ # CI/CD workflows
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├── pyproject.toml # Main project configuration
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└── requirements.txt # Pinned dependencies
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```
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---
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## Build and Development Commands
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### Setup (REQUIRED before any development)
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```bash
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# Install in editable mode (REQUIRED for tests due to src/ layout)
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pip install -e .
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# Install with all platform dependencies
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pip install -e ".[all-llms]"
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# Install specific platforms only
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pip install -e ".[gemini]" # Google Gemini support
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pip install -e ".[openai]" # OpenAI ChatGPT support
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pip install -e ".[mcp]" # MCP server dependencies
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```
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**CRITICAL:** The project uses a `src/` layout. Tests WILL FAIL unless you install with `pip install -e .` first.
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### Building
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```bash
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# Build package using uv (recommended)
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uv build
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# Or using standard build
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python -m build
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# Publish to PyPI
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uv publish
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```
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### Running Tests
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**CRITICAL:** Never skip tests - all tests must pass before commits.
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```bash
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# All tests (must run pip install -e . first!)
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pytest tests/ -v
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# Specific test file
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pytest tests/test_scraper_features.py -v
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pytest tests/test_mcp_fastmcp.py -v
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# With coverage
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pytest tests/ --cov=src/skill_seekers --cov-report=term --cov-report=html
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# Single test
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pytest tests/test_scraper_features.py::test_detect_language -v
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# E2E tests
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pytest tests/test_e2e_three_stream_pipeline.py -v
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```
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**Test Architecture:**
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- 76 test files covering all features
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- CI Matrix: Ubuntu + macOS, Python 3.10-3.13
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- 1200+ tests passing
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- Test markers: `slow`, `integration`, `e2e`, `venv`, `bootstrap`
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---
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## Code Style Guidelines
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### Linting and Formatting
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```bash
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# Run ruff linter
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ruff check src/ tests/
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# Run ruff formatter check
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ruff format --check src/ tests/
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# Auto-fix issues
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ruff check src/ tests/ --fix
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ruff format src/ tests/
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# Run mypy type checker
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mypy src/skill_seekers --show-error-codes --pretty
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```
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### Style Rules (from pyproject.toml)
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- **Line length:** 100 characters
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- **Target Python:** 3.10+
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- **Enabled rules:** E, W, F, I, B, C4, UP, ARG, SIM
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- **Import sorting:** isort style with `skill_seekers` as first-party
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### Code Conventions
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1. **Use type hints** where practical (gradual typing approach)
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2. **Docstrings:** Use Google-style or standard docstrings
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3. **Error handling:** Use specific exceptions, provide helpful messages
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4. **Async code:** Use `asyncio`, mark tests with `@pytest.mark.asyncio`
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5. **File naming:** Use snake_case for all Python files
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---
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## Architecture Patterns
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### Platform Adaptor Pattern (Strategy Pattern)
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All platform-specific logic is encapsulated in adaptors:
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```python
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from skill_seekers.cli.adaptors import get_adaptor
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# Get platform-specific adaptor
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adaptor = get_adaptor('gemini') # or 'claude', 'openai', 'markdown'
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# Package skill
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adaptor.package(skill_dir='output/react/', output_path='output/')
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# Upload to platform
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adaptor.upload(
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package_path='output/react-gemini.tar.gz',
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api_key=os.getenv('GOOGLE_API_KEY')
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)
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```
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### CLI Architecture (Git-style)
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Entry point: `src/skill_seekers/cli/main.py`
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The CLI uses subcommands that delegate to existing modules:
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```python
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# skill-seekers scrape --config react.json
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# Transforms to: doc_scraper.main() with modified sys.argv
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```
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**Available subcommands:**
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- `config` - Configuration wizard
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- `scrape` - Documentation scraping
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- `github` - GitHub repository scraping
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- `pdf` - PDF extraction
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- `unified` - Multi-source scraping
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- `analyze` - Local codebase analysis
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- `enhance` - AI enhancement
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- `package` - Package skill
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- `upload` - Upload to platform
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- `install` / `install-agent` - Complete workflow
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### MCP Server Architecture
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Two implementations:
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- `server_fastmcp.py` - Modern, decorator-based (recommended, 708 lines)
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- `server.py` - Legacy implementation (2200 lines)
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Tools are organized by category:
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- Config tools (3)
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- Scraping tools (8)
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- Packaging tools (4)
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- Splitting tools (2)
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- Source tools (4)
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---
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## Testing Instructions
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### Test Categories
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| Marker | Description |
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|--------|-------------|
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| `slow` | Tests taking >5 seconds |
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| `integration` | Requires external services (APIs) |
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| `e2e` | End-to-end tests (resource-intensive) |
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| `venv` | Requires virtual environment setup |
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| `bootstrap` | Bootstrap skill specific |
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### Running Specific Test Categories
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```bash
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# Skip slow tests
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pytest tests/ -v -m "not slow"
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# Run only integration tests
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pytest tests/ -v -m integration
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# Run E2E tests
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pytest tests/ -v -m e2e
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```
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### Test Configuration (pytest.ini in pyproject.toml)
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```toml
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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python_files = ["test_*.py"]
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addopts = "-v --tb=short --strict-markers"
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asyncio_mode = "auto"
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```
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---
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## Git Workflow
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### Branch Structure
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```
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main (production)
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↑
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│ (only maintainer merges)
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│
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development (integration) ← default branch for PRs
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↑
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│ (all contributor PRs go here)
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│
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feature branches
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```
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- **`main`** - Production, always stable, protected
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- **`development`** - Active development, default for PRs
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- **Feature branches** - Your work, created from `development`
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### Creating a Feature Branch
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```bash
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# 1. Checkout development
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git checkout development
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git pull upstream development
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# 2. Create feature branch
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git checkout -b my-feature
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# 3. Make changes, commit, push
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git add .
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git commit -m "Add my feature"
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git push origin my-feature
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# 4. Create PR targeting 'development' branch
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```
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---
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## CI/CD Configuration
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### GitHub Actions Workflows
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**`.github/workflows/tests.yml`:**
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- Runs on: push/PR to `main` and `development`
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- Lint job: Ruff + MyPy
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- Test matrix: Ubuntu + macOS, Python 3.10-3.12
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- Coverage: Uploads to Codecov
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**`.github/workflows/release.yml`:**
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- Triggered on version tags
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- Builds and publishes to PyPI
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### Pre-commit Checks (Manual)
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```bash
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# Before committing, run:
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ruff check src/ tests/
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ruff format --check src/ tests/
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pytest tests/ -v -x # Stop on first failure
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```
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---
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## Security Considerations
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### API Keys and Secrets
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1. **Never commit API keys** to the repository
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2. **Use environment variables:**
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- `ANTHROPIC_API_KEY` - Claude AI
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- `GOOGLE_API_KEY` - Google Gemini
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- `OPENAI_API_KEY` - OpenAI
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- `GITHUB_TOKEN` - GitHub API
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3. **Configuration storage:**
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- Stored at `~/.config/skill-seekers/config.json`
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- Permissions: 600 (owner read/write only)
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### Rate Limit Handling
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- GitHub API has rate limits (5000 requests/hour for authenticated)
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- The tool has built-in rate limit handling with retry logic
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- Use `--non-interactive` flag for CI/CD environments
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### Custom API Endpoints
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Support for Claude-compatible APIs (e.g., GLM-4.7):
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```bash
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export ANTHROPIC_API_KEY=your-glm-47-api-key
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export ANTHROPIC_BASE_URL=https://glm-4-7-endpoint.com/v1
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```
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---
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## Common Development Tasks
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### Adding a New CLI Command
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1. Create module in `src/skill_seekers/cli/my_command.py`
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2. Implement `main()` function with argument parsing
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3. Add entry point in `pyproject.toml`:
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```toml
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[project.scripts]
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skill-seekers-my-command = "skill_seekers.cli.my_command:main"
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```
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4. Add subcommand handler in `src/skill_seekers/cli/main.py`
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5. Add tests in `tests/test_my_command.py`
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### Adding a New Platform Adaptor
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1. Create `src/skill_seekers/cli/adaptors/my_platform.py`
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2. Inherit from `SkillAdaptor` base class
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3. Implement required methods: `package()`, `upload()`, `enhance()`
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4. Register in `src/skill_seekers/cli/adaptors/__init__.py`
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5. Add optional dependencies in `pyproject.toml`
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6. Add tests in `tests/test_adaptors/`
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### Adding an MCP Tool
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1. Implement tool logic in `src/skill_seekers/mcp/tools/category_tools.py`
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2. Register in `src/skill_seekers/mcp/server_fastmcp.py`
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3. Add test in `tests/test_mcp_fastmcp.py`
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---
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## Documentation
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### Project Documentation
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- **README.md** - Main project documentation
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- **README.zh-CN.md** - Chinese translation
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- **CLAUDE.md** - Detailed implementation guidance
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- **QUICKSTART.md** - Quick start guide
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- **CONTRIBUTING.md** - Contribution guidelines
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- **docs/** - Comprehensive documentation (54 files)
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### Configuration Documentation
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Preset configs are in `configs/` directory:
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- `godot.json` - Godot Engine
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- `react.json` - React
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- `vue.json` - Vue.js
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- `fastapi.json` - FastAPI
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- `*_unified.json` - Multi-source configs
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---
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## Troubleshooting
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### Common Issues
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**ImportError: No module named 'skill_seekers'**
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- Solution: Run `pip install -e .`
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**Tests failing with "package not installed"**
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- Solution: Ensure you ran `pip install -e .` in the correct virtual environment
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**MCP server import errors**
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- Solution: Install with `pip install -e ".[mcp]"`
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**Type checking failures**
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- MyPy is configured to be lenient (gradual typing)
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- Focus on critical paths, not full coverage
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### Getting Help
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- Check **TROUBLESHOOTING.md** for detailed solutions
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- Review **docs/FAQ.md** for common questions
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- Visit https://skillseekersweb.com/ for documentation
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- Open an issue on GitHub with:
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- Clear title and description
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- Steps to reproduce
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- Expected vs actual behavior
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- Environment details (OS, Python version)
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- Error messages and stack traces
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---
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## Key Dependencies
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### Core Dependencies
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- `requests>=2.32.5` - HTTP requests
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- `beautifulsoup4>=4.14.2` - HTML parsing
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- `PyGithub>=2.5.0` - GitHub API
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- `GitPython>=3.1.40` - Git operations
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- `httpx>=0.28.1` - Async HTTP
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- `anthropic>=0.76.0` - Claude AI API
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- `PyMuPDF>=1.24.14` - PDF processing
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- `pydantic>=2.12.3` - Data validation
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- `click>=8.3.0` - CLI framework
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### Optional Dependencies
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- `mcp>=1.25` - MCP server
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- `google-generativeai>=0.8.0` - Gemini support
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- `openai>=1.0.0` - OpenAI support
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### Dev Dependencies
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- `pytest>=8.4.2` - Testing framework
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- `pytest-asyncio>=0.24.0` - Async test support
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- `pytest-cov>=7.0.0` - Coverage
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- `ruff>=0.14.13` - Linting/formatting
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- `mypy>=1.19.1` - Type checking
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---
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*This document is maintained for AI coding agents. For human contributors, see README.md and CONTRIBUTING.md.*
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