Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
45,100 skills from 2,196 repositories · updated 6 hours ago
45,100 skills
- paper-writewanshuiyin/Auto-claude-code-research-in-sleepDraft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.ScienceNo warnings★ 18.1K↓ —
- proof-orchestratorwanshuiyin/Auto-claude-code-research-in-sleepManage a stateful, run-directory-based proof project: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.WritingNo warnings★ 18.1K↓ —
- idea-discovery-robotwanshuiyin/Auto-claude-code-research-in-sleepWorkflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.EngineeringNo warnings★ 18.1K↓ —
- invention-structuringwanshuiyin/Auto-claude-code-research-in-sleepStructure a raw invention idea into a formal invention disclosure. Use when user says "构建发明", "structure invention", "发明构建", "invention disclosure", or wants to formalize a rough idea into a patent-ready structure.OtherNo warnings★ 18.1K↓ —
- patent-novelty-checkwanshuiyin/Auto-claude-code-research-in-sleepAssess patent novelty and non-obviousness against prior art. Use when user says "专利查新", "patent novelty", "可专利性评估", "patentability check", or wants to evaluate if an invention is patentable.OtherNo warnings★ 18.1K↓ —
- web-debug-searchwanshuiyin/Auto-claude-code-research-in-sleepSearch GitHub, Stack Exchange, Chinese technical communities, official documentation, and general developer web sources for software errors, compatibility problems, API usage questions, and real-world workarounds. Use for debugging and discovery only; results are not paper-citation evidence.EngineeringNo warnings★ 18.1K↓ —Also in 1 other repo
- slime-rl-trainingOrchestra-Research/AI-Research-SKILLsProvides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.OtherNo warnings★ 14K↓ —
- gptqOrchestra-Research/AI-Research-SKILLsPost-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.DevOpsNo warnings★ 14K↓ —
- llamaindexOrchestra-Research/AI-Research-SKILLsData framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.PlanningNo warnings★ 14K↓ —
- llavaOrchestra-Research/AI-Research-SKILLsLarge Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.MediaNo warnings★ 14K↓ —
- gguf-quantizationOrchestra-Research/AI-Research-SKILLsGGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.DevOpsNo warnings★ 14K↓ —
- blip-2-vision-languageOrchestra-Research/AI-Research-SKILLsVision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.MediaNo warnings★ 14K↓ —
- plantuml-asciigithub/awesome-copilotGenerate ASCII art diagrams using PlantUML text mode. Use when user asks to create ASCII diagrams, text-based diagrams, terminal-friendly diagrams, or mentions plantuml ascii, text diagram, ascii art diagram. Supports: Converting PlantUML diagrams to ASCII art, Creating sequence diagrams, class diagrams, flowcharts in ASCII format, Generating Unicode-enhanced ASCII art with -utxt flagPlanningNo warnings★ 40.4K↓ —
- awq-quantizationOrchestra-Research/AI-Research-SKILLsActivation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.DevOpsNo warnings★ 14K↓ —
- fine-tuning-serving-openpiOrchestra-Research/AI-Research-SKILLsFine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.EngineeringNo warnings★ 14K↓ —
- hqq-quantizationOrchestra-Research/AI-Research-SKILLsHalf-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.DevOpsNo warnings★ 14K↓ —
- clipOrchestra-Research/AI-Research-SKILLsOpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.MediaNo warnings★ 14K↓ —
- interview-cheatsheetwanshuiyin/Auto-claude-code-research-in-sleepGenerate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab). Use when the user says '写面试 cheat sheet', '写一份 X 教程', '帮我准备 Y 面试题', '出一份 X 速查', or wants a 600-1000 line Chinese tutorial on a specific ML topic.PlanningNo warnings★ 18.1K↓ —
- peft-fine-tuningOrchestra-Research/AI-Research-SKILLsParameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.ProductivityNo warnings★ 14K↓ —
- monitor-experimentwanshuiyin/Auto-claude-code-research-in-sleepMonitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.OtherNo warnings★ 18.1K↓ —
- langchainOrchestra-Research/AI-Research-SKILLsFramework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.DevOpsNo warnings★ 14K↓ —
- constitutional-aiOrchestra-Research/AI-Research-SKILLsAnthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.OtherNo warnings★ 14K↓ —
- mamba-architectureOrchestra-Research/AI-Research-SKILLsState-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.PlanningNo warnings★ 14K↓ —
- paper-claim-auditwanshuiyin/Auto-claude-code-research-in-sleepZero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.ScienceNo warnings★ 18.1K↓ —
exa-search
wanshuiyin/Auto-claude-code-research-in-sleep
From the author
AI-powered web search via Exa with content extraction. Use when user says "exa search", "web search with content", "find similar pages", or needs broad web results beyond academic databases (arXiv, Semantic Scholar).
Install
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill exa-search -a claude-code
Installs to .claude/skills/exa-search/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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