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 10 hours ago
45,100 skills
- nemo-curatorOrchestra-Research/AI-Research-SKILLsGPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.MediaNo warnings★ 14K↓ —
- skillkrillinai/OpenCreatorFormerly KrillinAI, VideoTranslation and Dubbing Tool. Open-source AI workspace for creators, powered by Codex. Video downloading, video translation, create videos, images, voice, avatars, and edits with Agents in one place. Suitable for your Social Media like YouTube, TikTok, Instagram, etc.MediaNo warnings★ 13.9K↓ —
- faviconsickn33/agentic-awesome-skillsGenerate favicons from a source imageMediaNo warnings★ 48.5K↓ —
- proof-checkerwanshuiyin/Auto-claude-code-research-in-sleepRigorous mathematical proof verification and fixing workflow. Reads a LaTeX proof, identifies gaps via cross-model review (external reviewer backend, ultra reasoning), fixes each gap with full derivations, re-reviews, and generates an audit report. Use when user says "检查证明", "verify proof", "proof check", "审证明", "check this proof", or wants rigorous mathematical verification of a theory paper.ScienceNo warnings★ 18.1K↓ —
- stable-diffusion-image-generationOrchestra-Research/AI-Research-SKILLsState-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.MediaNo warnings★ 14K↓ —
- prompt-guardOrchestra-Research/AI-Research-SKILLsMeta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages). Deploy with HuggingFace or batch processing for RAG security.SecurityNo warnings★ 14K↓ —
- prompt-masternidhinjs/prompt-masterGenerates optimized prompts for AI tools. Activates only when the user explicitly asks to write, fix, improve, or adapt a prompt for a specific AI tool (LLM, Cursor, Midjourney, image AI, video AI, coding agents, etc.). Does not activate for general conversation, coding tasks, document writing, or other non-prompt-engineering work.MediaNo warnings★ 15.1K↓ —
- analyze-resultswanshuiyin/Auto-claude-code-research-in-sleepAnalyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.OtherNo warnings★ 18.1K↓ —
- outlinesOrchestra-Research/AI-Research-SKILLsGuarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation libraryEngineeringNo warnings★ 14K↓ —
- research-wikiwanshuiyin/Auto-claude-code-research-in-sleepPersistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.ScienceNo warnings★ 18.1K↓ —
- instructorOrchestra-Research/AI-Research-SKILLsExtract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output libraryOtherNo warnings★ 14K↓ —
- hunt-lfisickn33/agentic-awesome-skillsHunt Local File Inclusion (LFI), Remote File Inclusion (RFI), and Path TraversalOtherNo warnings★ 48.5K↓ —
- segment-anything-modelOrchestra-Research/AI-Research-SKILLsFoundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.MediaNo warnings★ 14K↓ —
- llamaguardOrchestra-Research/AI-Research-SKILLsMeta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.DevOpsNo warnings★ 14K↓ —
- llama-cppOrchestra-Research/AI-Research-SKILLsRuns LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.DevOpsNo warnings★ 14K↓ —
- proof-writerwanshuiyin/Auto-claude-code-research-in-sleepWrites rigorous mathematical proofs for ML/AI theory. Use when asked to prove a theorem, lemma, proposition, or corollary, fill in missing proof steps, formalize a proof sketch, 补全证明, 写证明, 证明某个命题, or determine whether a claimed proof can actually be completed under the stated assumptions.WritingNo warnings★ 18.1K↓ —
- patent-pipelinewanshuiyin/Auto-claude-code-research-in-sleepFull patent drafting pipeline from invention description to jurisdiction-formatted filing documents. Supports CN (CNIPA), US (USPTO), EP (EPO). Supports invention patents and utility models. Use when user says "写专利", "patent pipeline", "专利申请", "draft patent", "写权利要求书", or wants to draft a complete patent application.OtherNo warnings★ 18.1K↓ —
- deepxivwanshuiyin/Auto-claude-code-research-in-sleepSearch and progressively read open-access academic papers through DeepXiv. Use when the user wants layered paper access, section-level reading, trending papers, or DeepXiv-backed literature retrieval.ScienceNo warnings★ 18.1K↓ —
- issue-reporterCherryHQ/cherry-studio仅在用户点名 GitHub Issue、Bug Report 或 Feature Request 时使用；未点名 GitHub 的反馈改用 cherry-studio-feedback。OtherNo warnings★ 53K↓ —
- guidanceOrchestra-Research/AI-Research-SKILLsControl LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation frameworkScienceNo warnings★ 14K↓ —
- idea-discoverywanshuiyin/Auto-claude-code-research-in-sleepWorkflow 1: Full idea discovery pipeline to go from a broad research direction to validated, pilot-tested ideas. Use when user says "找idea全流程", "idea discovery pipeline", "从零开始找方向", or wants the complete idea exploration workflow.ScienceNo warnings★ 18.1K↓ —
- nemo-evaluator-sdkOrchestra-Research/AI-Research-SKILLsEvaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.DevOpsNo warnings★ 14K↓ —
- quantizing-models-bitsandbytesOrchestra-Research/AI-Research-SKILLsQuantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.ProductivityNo warnings★ 14K↓ —
- meta-optimizewanshuiyin/Auto-claude-code-research-in-sleepAnalyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when user says "优化技能", "meta optimize", "improve skills", "分析使用记录", or wants to optimize ARIS's own harness components based on accumulated experience.ProductivityNo warnings★ 18.1K↓ —
azure-communication-callautomation-java
microsoft/skills
OfficialDevOpsUpdated 19 hours ago
From the author
Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-powered call flows.
Install
npx skills add microsoft/skills --skill azure-communication-callautomation-java -a claude-code
Installs to .claude/skills/azure-communication-callautomation-java/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 93
Security100
Provenance100
Maintenance100
Licence100
Adoption56
Files (2)
- SKILL.md
- references/examples.md