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
- 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↓ —
- paper-illustrationwanshuiyin/Auto-claude-code-research-in-sleepGenerate publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Codex-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers.MediaNo warnings★ 18.1K↓ —
- golden-pdf-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumentsNo warnings★ 15.2K↓ —
- arxivwanshuiyin/Auto-claude-code-research-in-sleepSearch, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.ScienceNo warnings★ 18.1K↓ —
- presetmicrosoft/skillsIntelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).OfficialDevOpsNo warnings★ 3.1K↓ —Also in 3 other repos
- auto-review-loopwanshuiyin/Auto-claude-code-research-in-sleepAutonomous multi-round research review loop. Uses a fresh Codex agent or selected Gemini, Grok, or Claude Code reviewer, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.EngineeringNo warnings★ 18.1K↓ —
- grant-proposalwanshuiyin/Auto-claude-code-research-in-sleepDraft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.ScienceNo warnings★ 18.1K↓ —
- research-pipelinewanshuiyin/Auto-claude-code-research-in-sleepFull end-to-end research pipeline: from a broad research direction through idea discovery, experiments, and review all the way to a polished paper PDF. Use when user says "全流程", "full pipeline", "从找idea到投稿", "end-to-end research", or wants the complete autonomous research lifecycle.ScienceNo warnings★ 18.1K↓ —
- research-refinewanshuiyin/Auto-claude-code-research-in-sleepTurn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-6-Astra review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.ScienceNo warnings★ 18.1K↓ —
- semantic-scholarwanshuiyin/Auto-claude-code-research-in-sleepSearch published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.ScienceNo warnings★ 18.1K↓ —
- result-to-claimwanshuiyin/Auto-claude-code-research-in-sleepUse when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.ScienceNo warnings★ 18.1K↓ —
- tensorrt-llmOrchestra-Research/AI-Research-SKILLsOptimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.DevOpsNo warnings★ 14K↓ —
- ablation-plannerwanshuiyin/Auto-claude-code-research-in-sleepUse when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.PlanningNo warnings★ 18.1K↓ —
- ablation-plannerwanshuiyin/Auto-claude-code-research-in-sleepUse when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.PlanningNo warnings★ 18.1K↓ —
- result-to-claimwanshuiyin/Auto-claude-code-research-in-sleepUse when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. A secondary Codex agent evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.ScienceNo warnings★ 18.1K↓ —
- serverless-modalwanshuiyin/Auto-claude-code-research-in-sleepRun GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.DevOpsNo 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↓ —
- skill-builderyusufkaraaslan/Skill_SeekersAutomatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.OtherNo warnings★ 15.2K↓ —
- 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↓ —
- distributed-llm-pretraining-torchtitanOrchestra-Research/AI-Research-SKILLsProvides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.OtherNo warnings★ 14K↓ —
- optimizing-attention-flashOrchestra-Research/AI-Research-SKILLsOptimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.ProductivityNo warnings★ 14K↓ —
- 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↓ —
- auto-review-loopwanshuiyin/Auto-claude-code-research-in-sleepAutonomous multi-round research review loop. In Copilot CLI it defaults to the native complementary rubber-duck subagent with host-event model evidence; elsewhere it uses Codex, while explicit external reviewer overrides remain available. Implements fixes and re-reviews until a policy-approved positive assessment or max rounds is reached.EngineeringNo warnings★ 18.1K↓ —
- research-refinewanshuiyin/Auto-claude-code-research-in-sleepTurn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-6-Astra review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.ScienceNo warnings★ 18.1K↓ —
azure-monitor-query-py
microsoft/skills
OfficialDevOpsUpdated 15 hours ago
From the author
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics. Triggers: "azure-monitor-query", "LogsQueryClient", "MetricsQueryClient", "Log Analytics", "Kusto queries", "Azure metrics".
Install
npx skills add microsoft/skills --skill azure-monitor-query-py -a claude-code
Installs to .claude/skills/azure-monitor-query-py/ · 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 onlyUses the networkLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 93
Security100
Provenance100
Maintenance100
Licence100
Adoption56
Files (3)
- SKILL.md
- references/capabilities.md
- references/non-hero-scenarios.md