Discover research llm ai skills, compare source repositories and read the instructions for each workflow.
Guidance for using Claude Code component architecture and choosing between agents, skills, commands, and hooks. Helps decide which component type fits a use case, understand delegation and isolation, debug cros...
Interpretive guidance for designing Claude Code hooks. Helps you understand hook lifecycle, when to use hooks vs other patterns, and common pitfalls. ALWAYS use when creating or reviewing hooks.
Interpretive guidance for Claude Code memory management system. Helps choose between memory locations, organize modular rules, use path-specific rules, and avoid common pitfalls. Use when setting up CLAUDE.md f...
Interpretive guidance for designing Claude Code plugins. Helps you understand plugin architecture, marketplace distribution, and when plugins are the right pattern. Use when creating or reviewing plugins.
Meta-skill that teaches how to design Claude Code skills following the Box Factory philosophy. Helps you understand when to create skills, how to structure them for low maintenance, and how to add value beyond...
Interpretive guidance for designing Claude Code sub-agents. Helps apply official documentation effectively and avoid common pitfalls. ALWAYS use when creating or reviewing sub-agents (aka agents or subagents).
Interpretive guidance for designing Claude Code slash commands. Helps you apply official documentation effectively and create high-quality commands. Use when creating or reviewing slash commands.
Deploy and manage Docker containers on Cloudflare's global network alongside Workers. Use when building applications that need to run Python code, process large files (multi-GB zips, video transcoding), execute...
EXPAND vague prompts into precise, platform-optimized instructions. Detects target platform (Claude, GPT, Gemini, Midjourney, Sora, etc.) and applies appropriate prompting patterns. Use when user says "coggle",...
Brief description of what this Skill does and when to use it. This field is critical for Claude to discover when to invoke your skill.
Structure meeting transcripts into organized notes with action items, decisions, and key points. Use when processing meeting recordings or creating meeting summaries.
Create new Claude Agent Skills. Use when asked to create, build, or develop a skill.
Expert guidance for XState state machines, actor model patterns, React integration, and statecharts. Use when implementing state machines, managing complex application state, using the actor model for concurren...
LlamaIndex Wolfram Alpha tool for computational knowledge queries, math solving, scientific calculations, and agent integration. Triggers: wolfram alpha, computational query, math solver, scientific calculation...
Natural Language Processing utilities for PyTorch (Legacy). Includes tokenizers, vocabulary building, and DataPipe-based dataset handling for text processing pipelines. (torchtext, tokenizer, vocab, datapipe, r...
Build RAG (Retrieval-Augmented Generation) agents with Google ADK and Vertex AI RAG Engine. Use when implementing document Q&A, knowledge base search, or citation-backed responses. Covers VertexAiRagRetrieval t...
Techniques for ensuring LLM responses adhere to strict JSON schemas, utilizing Pydantic models, JSON mode, and schema-based refusals. Triggers: structured-output, pydantic, json-schema, json-mode, llm-response-...
Deploying fine-tuned models for production inference using native kernel optimization, vLLM, or SGLang. Triggers: inference, serving, vllm, sglang, for_inference, model merging, openai api.
Build RAG systems with Ollama local + cloud models. Latest cloud models include DeepSeek-V3.2 (GPT-5 level), Qwen3-Coder-480B (1M context), MiniMax-M2. Use for document Q&A, knowledge bases, and agentic RAG. Co...
Core fundamentals of Unsloth for fast LLM fine-tuning, covering FastLanguageModel setup, optimized gradient checkpointing, and native inference acceleration (triggers: unsloth, FastLanguageModel, from_pretraine...
Exporting fine-tuned models to GGUF format for deployment in llama.cpp, Ollama, and local serving tools. Triggers: gguf, quantization export, llama.cpp, ollama, save_pretrained_gguf, modelfile.
Design and operate multi-agent orchestration patterns (ReAct loops, evaluator-optimizer, orchestrator-workers, tool routing) for LLM systems. Use when building or debugging agent workflows, tool-use loops, or m...
Guidance on selecting and configuring supported model architectures like Llama 4, DeepSeek-R1, and Qwen3. Triggers: llama 4, deepseek-r1, qwen3, gemma 3, model selection, instruct vs base.
Define and run tool-calling patterns for LLMs (schema design, call loops, validation, parallel calls). Use when building function/tool calling workflows or debugging tool selection and arguments; triggers: tool...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.