MCPInstall

python-skills

Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.

Installs
68
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/llama-farm/llamafarm --skill python-skills
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads python-skills automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Python Skills for LlamaFarm

Shared Python best practices and code review checklists for all Python components in the LlamaFarm monorepo.

Applicable Components

ComponentPathPythonKey Dependencies
Serverserver/3.12+FastAPI, Celery, Pydantic, structlog
RAGrag/3.11+LlamaIndex, ChromaDB, Celery
Universal Runtimeruntimes/universal/3.11+PyTorch, transformers, FastAPI
Configconfig/3.11+Pydantic, JSONSchema
Commoncommon/3.10+HuggingFace Hub

Quick Reference

TopicFileKey Points
Patternspatterns.mdDataclasses, Pydantic, comprehensions, imports
Asyncasync.mdasync/await, asyncio, concurrent execution
Typingtyping.mdType hints, generics, protocols, Pydantic
Testingtesting.mdPytest fixtures, mocking, async tests
Errorserror-handling.mdCustom exceptions, logging, context managers
Securitysecurity.mdPath traversal, injection, secrets, deserialization

Code Style

LlamaFarm uses ruff with shared configuration in ruff.toml:

line-length = 88
target-version = "py311"
select = ["E", "F", "I", "B", "UP", "SIM"]

Key rules:

  • E, F: Core pyflakes and pycodestyle
  • I: Import sorting (isort)
  • B: Bugbear (common pitfalls)
  • UP: Upgrade syntax to modern Python
  • SIM: Simplify code patterns

Architecture Patterns

Settings with pydantic-settings

from pydantic_settings import BaseSettings

class Settings(BaseSettings, env_file=".env"):
    LOG_LEVEL: str = "INFO"
    HOST: str = "0.0.0.0"
    PORT: int = 14345

settings = Settings()  # Singleton at module level

Structured Logging with structlog

from core.logging import FastAPIStructLogger  # Server
from core.logging import RAGStructLogger      # RAG
from core.logging import UniversalRuntimeLogger  # Runtime

logger = FastAPIStructLogger(__name__)
logger.info("Operation completed", extra={"count": 10, "duration_ms": 150})

Abstract Base Classes for Extensibility

from abc import ABC, abstractmethod

class Component(ABC):
    def __init__(self, name: str, config: dict[str, Any] | None = None):
        self.name = name or self.__class__.__name__
        self.config = config or {}

    @abstractmethod
    def process(self, documents: list[Document]) -> ProcessingResult:
        pass

Dataclasses for Internal Data

from dataclasses import dataclass, field

@dataclass
class Document:
    content: str
    metadata: dict[str, Any] = field(default_factory=dict)
    id: str = field(default_factory=lambda: str(uuid.uuid4()))

Pydantic Models for API Boundaries

from pydantic import BaseModel, Field, ConfigDict

class EmbeddingRequest(BaseModel):
    model: str
    input: str | list[str]
    encoding_format: Literal["float", "base64"] | None = "float"

    model_config = ConfigDict(str_strip_whitespace=True)

Directory Structure

Each Python component follows this structure:

component/
├── pyproject.toml     # UV-managed dependencies
├── core/              # Core functionality
│   ├── __init__.py
│   ├── settings.py    # Pydantic Settings
│   └── logging.py     # structlog setup
├── services/          # Business logic (server)
├── models/            # ML models (runtime)
├── tasks/             # Celery tasks (rag)
├── utils/             # Utility functions
└── tests/
    ├── conftest.py    # Shared fixtures
    └── test_*.py

Review Checklist Summary

When reviewing Python code in LlamaFarm:

  1. Patterns (Medium priority)

    • Modern Python syntax (3.10+ type hints)
    • Dataclass vs Pydantic used appropriately
    • No mutable default arguments
  2. Async (High priority)

    • No blocking calls in async functions
    • Proper asyncio.Lock usage
    • Cancellation handled correctly
  3. Typing (Medium priority)

    • Complete return type hints
    • Generic types parameterized
    • Pydantic v2 patterns
  4. Testing (Medium priority)

    • Fixtures properly scoped
    • Async tests use pytest-asyncio
    • Mocks cleaned up
  5. Errors (High priority)

    • Custom exceptions with context
    • Structured logging with extra dict
    • Proper exception chaining
  6. Security (Critical priority)

    • Path traversal prevention
    • Input sanitization
    • Safe deserialization

See individual topic files for detailed checklists with grep patterns.

FAQ

What does the python-skills skill do?

Shared Python best practices for LlamaFarm. Covers patterns, async, typing, testing, error handling, and security.

How do I install python-skills?

Run npx skills add https://github.com/llama-farm/llamafarm --skill python-skills in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/python-skills/ (personal) or .claude/skills/python-skills/ (project).

Which AI agents can use python-skills?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is python-skills safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains python-skills?

It is published by llama-farm in llama-farm/llamafarm. It has 68 recorded installs.

More from llama-farm/llamafarm

View all →

code-review

llama-farm/llamafarm

Comprehensive code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.

commit-push-pr

llama-farm/llamafarm

Open the skill to read its SKILL.md instructions.

electron-skills

llama-farm/llamafarm

Electron patterns for LlamaFarm Desktop. Covers main/renderer processes, IPC, security, and packaging.

Security85 installs

typescript-skills

llama-farm/llamafarm

Shared TypeScript best practices for Designer and Electron subsystems.

react-skills

llama-farm/llamafarm

React 18 patterns for LlamaFarm Designer. Covers components, hooks, TanStack Query, and testing.

rag-skills

llama-farm/llamafarm

RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.

AI & Agents58 installs

Popular testing & qa skills

View category →

tdd

mattpocock/skills

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

Testing & QA1.2M installs

grilling

mattpocock/skills

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

Testing & QA996.2K installs

migrate-to-shoehorn

mattpocock/skills

Migrate test files from as type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace as in tests, or needs partial test data.

Testing & QA484.1K installs

run-train

lllllllama/rigorpilot-skills

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized trainoutputs/. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.

Testing & QA337.8K installs

test-driven-development

obra/superpowers

Use when implementing any feature or bugfix, before writing implementation code

Testing & QA261.8K installs

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work

Testing & QA216.8K installs