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Llama Farm publishes skills that help AI agents build and maintain the LlamaFarm codebase, covering React 18 and TailwindCSS front ends, Go CLI tooling with Cobra and Bubbletea, Python and TypeScript best practices, and PyTorch and Transformers model serving with FastAPI. Their collection stands out for its subsystem focus, with separate skills for runtime device and memory management, Go error handling and testing, and a Reflect skill that proposes improvements to the other skills from past sessions.
Llamafarm
19 skills · 836 stars · Apache-2.0
Cli Skills CLI best practices for LlamaFarm.
Code Review Comprehensive code review for diffs.
Commit Push Pr Commit changes, push to GitHub, and open a PR.
Common Skills Best practices for the Common utilities package in LlamaFarm.
Config Skills Configuration module patterns for LlamaFarm.
Designer Skills Designer subsystem patterns for LlamaFarm.
Electron Skills Electron patterns for LlamaFarm Desktop.
Fix Ci Fetch GitHub CI failure information, analyze root causes, reproduce locally, and propose a fix plan.
Generate Subsystem Skills Generate specialized skills for each subsystem in the monorepo.
Go Skills Shared Go best practices for LlamaFarm CLI.
Python Skills Shared Python best practices for LlamaFarm.
Rag Skills RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers.
React Skills React 18 patterns for LlamaFarm Designer.
Reflect Analyze the current session and propose improvements to skills.
Runtime Skills Universal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving.
Server Skills Server-specific best practices for FastAPI, Celery, and Pydantic.
Temp Files Guidelines for creating temporary files in system temp directory.
Typescript Skills Shared TypeScript best practices for Designer and Electron subsystems.
Wt Manage LlamaFarm worktrees for isolated parallel development.