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คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
uvx patchwork-conventions==0.1.7Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
claude mcp add io.github.sainarayana-b-patchwork -- uvx patchwork-conventions==0.1.7รันในเทอร์มินัล
{ "mcpServers": { "io.github.sainarayana-b-patchwork": { "command": "uvx", "args": [ "patchwork-conventions==0.1.7" ] } }}claude_desktop_config.json
URL แบบรีโมตหรือคำสั่งบนเครื่องของคุณ? การติดตั้งสองแบบต่างกันอย่างไร
รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดEvery team that uses AI coding assistants hits the same wall: Claude writes getUserById in a codebase that uses get_user_by_id. Cursor creates components/userCard.tsx in a project that uses user-card.tsx. The agent invented a response shape that doesn't match the rest of the API.
You write a CLAUDE.md manually. It goes stale in two weeks. You write it again.
patchwork automates this. It scans your actual source code using AST analysis and detects what your team really does — not what you think you do.
pip install patchwork-conventions
cd your-project
patchwork scan
That's it. You'll get a CONVENTIONS.md like this:
# CONVENTIONS.md
> Auto-generated by patchwork on 2026-06-25
## Tech Stack
**Language:** python
**Runtime:** Python >=3.11
**Package Manager:** uv
**Frameworks:** fastapi, sqlalchemy
**Linters:** ruff
**Formatters:** ruff, black
## Naming Conventions
### Python
- **Functions:** `snake_case` (97% consistent)
- Examples: `get_user`, `parse_response`, `create_session`
- **Classes:** `PascalCase` (100% consistent)
- Examples: `UserService`, `AuthHandler`, `DatabaseClient`
- **Constants:** `SCREAMING_SNAKE`
- Examples: `MAX_RETRIES`, `API_BASE_URL`
- **Files:** `snake_case`
- **Private prefix:** `_`
- **Test functions:** prefix `test_`
## Project Structure
**Source root:** `src/`
**Organisation:** layer-based
**Tests:** separate (`tests/`)
**Key directories:**
- `src/` — source root
- `tests/` — test suite
- `migrations/` — database migrations
## Error Handling
### Python
- **Pattern:** try/except
- **Propagation:** raise
- **Logging:** `structlog`
- **Custom exception naming:** Error suffix
- `ValidationError`, `AuthError`, `NotFoundError`
## Testing Conventions
### Python
- **Framework:** pytest
- **Coverage:** 34 test files / 89 source files (38% ratio)
- **Assertions:** `assert(...)`
- **Coverage tool:** `pytest-cov`
- **Patterns:** fixtures, factories
## Git Conventions
- **Commit style:** conventional commits
- **Examples:** `feat(auth): add JWT refresh`, `fix(api): handle null user`
- **Branch naming:** feature/name + fix/name
# Generate CONVENTIONS.md
patchwork scan
# Generate for a specific path
patchwork scan /path/to/project
# Generate AGENTS.md
patchwork scan --agents-md
# Append to CLAUDE.md
patchwork scan --claude-md
# Output JSON (for programmatic use)
patchwork scan --json
# Print to stdout (don't write file)
patchwork scan --stdout
# Limit to specific languages
patchwork scan --lang python --lang typescript
# Re-scan and update, preserving manual edits
patchwork update
# Show what would change
patchwork diff
# Print detected conventions to terminal
patchwork show
# Auto-watch mode (regenerate on change)
patchwork watch
# Start MCP server
patchwork serve --stdio # for Claude Code
patchwork serve --port 3742 # HTTP mode
patchwork scan # run once
# CONVENTIONS.md is automatically read by Claude Code
patchwork scan --claude-md
Claude Code — add to ~/.claude.json (or run claude mcp add interactively):
{
"mcpServers": {
"patchwork": {
"command": "patchwork",
"args": ["serve", "/path/to/your/project", "--stdio"]
}
}
}
Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"patchwork": {
"command": "patchwork",
"args": ["serve", "/path/to/your/project", "--stdio"]
}
}
}
Cursor — add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"patchwork": {
"command": "patchwork",
"args": ["serve", ".", "--stdio"]
}
}
}
Then your AI agent can use 8 on-demand tools:
Copy SKILL.md from this repo to ~/.claude/skills/patchwork/SKILL.md to get /patchwork slash commands.
# Keep CONVENTIONS.md updated as you code
patchwork watch &
# Or in CI — fail if conventions changed
patchwork diff || (patchwork update && git add CONVENTIONS.md && git commit -m "chore: update conventions")
from patchwork import scan
from patchwork.scanner import ScanOptions
from pathlib import Path
# Full scan
report = scan(ScanOptions(root=Path(".")))
# Render to markdown
print(report.to_markdown())
# Render to JSON
import json
data = json.loads(report.to_json())
# Access specific results
naming = report.naming.get("python")
print(f"Functions: {naming.functions.style} ({naming.functions.confidence:.0%})")
print(f"Examples: {naming.functions.examples}")
structure = report.structure
print(f"Source root: {structure.source_root}")
print(f"Organisation: {structure.organisation}")
Install full language support:
pip install 'patchwork-conventions[full]'
your codebase
│
▼
ConfigDetector ← reads package.json, pyproject.toml, go.mod, Cargo.toml
│
▼
File discovery ← respects .gitignore, skips node_modules etc.
│
▼
Per-language AST ← tree-sitter parses every file into a syntax tree
│
├── NamingMiner → extracts function/class/variable names, classifies style
├── ImportMiner → detects import patterns, aliases, barrel files
├── StructureMiner → analyses directory layout, test co-location
├── ErrorHandlingMiner → detects try/catch patterns, logging, custom exceptions
├── TestingMiner → identifies framework, assertion style, mocking
├── APIPatternMiner → finds response shapes, ORMs, route styles
└── GitPatternMiner → mines commit history, branches, co-change pairs
│
▼
ConventionReport
│
├── CONVENTIONS.md (default)
├── AGENTS.md (--agents-md)
├── CLAUDE.md (--claude-md, appends)
└── JSON (--json)
All analysis is 100% local — no API calls, no telemetry, no data leaves your machine.
On a 1,000-file TypeScript monorepo:
On a 500-file Python project:
Results are deterministic — same codebase always produces the same output.
git clone https://github.com/yourusername/patchwork
cd patchwork
pip install -e '.[dev]'
pytest
Pull requests welcome. See CONTRIBUTING.md.
MIT — free for personal and commercial use.
claude-code · agent-skills · mcp · context-engineering · hallucination-detection · code-conventions · static-analysis · tree-sitter · developer-tools · ai-coding
Scan any codebase, generate CONVENTIONS.md, expose conventions as MCP tools for AI agents.
{ "mcpServers": { "io.github.sainarayana-b-patchwork": { "command": "uvx", "args": [ "patchwork-conventions==0.1.7" ] } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Patchwork — Codebase Conventions For AI Agents ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-09 Scan any codebase, generate CONVENTIONS.md, expose conventions as MCP tools for AI agents.