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 7 hours ago
45,100 skills
- golden-jupyter-diryusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter_dir golden buildTestingNo warnings★ 15.2K↓ —
- long-contextOrchestra-Research/AI-Research-SKILLsExtend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers rotary embeddings, attention biases, interpolation methods, and extrapolation strategies for LLMs.ProductivityNo warnings★ 14K↓ —
- eas-updateexpo/skillsConfigure and use EAS Update for over-the-air JavaScript and asset updates with expo-updates and EAS CLI. Use when setting up OTA updates, running eas update:configure or eas update, publishing to preview/staging/production channels, explaining branches/channels/runtime versions, testing updates, or debugging why an installed build still shows old code. Load for TestFlight, preview, or production updates that do not appear, including questions about cold launches or reopening the app. Not for update health metrics; use eas-update-insights for adoption, crashes, and rollout monitoring.OfficialTestingNo warnings★ 3K↓ —
- opencreator-runtimekrillinai/OpenCreatorOpenCreator 内部 Creator Agent 的稳定运行规则，仅由应用自动安装和激活。OtherNo warnings★ 13.9K↓ —
- eas-observeexpo/skillsUse for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive and ObserveInteractiveMarker, the useObserve hook, the Expo Router / React Navigation integrations for per-route metrics, user-defined events via `Observe.logEvent`, error reporting via ObserveErrorBoundary and `Observe.reportError`, native crash reporting, source map upload for symbolicated stack traces, and runtime config such as sampleRate and dispatchInDebug), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:session`, `observe:versions`, `observe:errors`, `observe:event`), interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate/device/network params for triaging slow startups), or shipping an Observe integration inside a third-party package.OfficialEngineeringNo warnings★ 3K↓ —
- ray-trainOrchestra-Research/AI-Research-SKILLsDistributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.OtherNo warnings★ 14K↓ —
- expo-examplesexpo/skillsExpo's official example projects - the expo/examples repo of ~70 `with-*` integrations (Stripe, Clerk, Supabase, OpenAI, maps, Reanimated, SQLite, Skia, NativeWind, and more). Use when integrating a third-party library or service into an existing Expo app and you want the canonical, version-matched pattern to adapt, or when scaffolding a new project from one with `npx create-expo --example`.OfficialOtherNo warnings★ 3K↓ —
- thinkAgriciDaniel/claude-obsidianApply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.PlanningNo warnings★ 15.8K↓ —
- kqlmicrosoft/skillsKQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.OfficialDevOpsNo warnings★ 3.1K↓ —
- stripe-projectsstripe/aiUse when the user wants to provision infrastructure or third-party services using Stripe Projects. Triggers: "I need a database", "set up auth", "add caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.OfficialDevOpsNo warnings★ 2K↓ —Also in 4 other repos
- auto-paper-improvement-loopwanshuiyin/Auto-claude-code-research-in-sleepAutonomously improve a generated paper via Claude review through claude-review MCP → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.ScienceNo 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↓ —
- fine-tuning-with-trlOrchestra-Research/AI-Research-SKILLsFine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.OtherNo warnings★ 14K↓ —
- paper-poster-htmlwanshuiyin/Auto-claude-code-research-in-sleepDEFAULT poster pipeline — build an academic conference poster (ICML/NeurIPS/ICLR/CVPR/...) as a single HTML/CSS file with measurement-driven hard gates, real paper figures, a two-hue design-token system, and print-ready PDF via headless Chromium. Use when the user says "做海报", "poster", "conference poster", "paper poster", or asks to design/redo a research poster.ScienceNo warnings★ 18.1K↓ —
- golden-pptx-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumentsNo warnings★ 15.2K↓ —
- natural-writingflutter/agent-pluginsContains well-defined rules for creating natural, accurate, and readable writing. Use whenever authoring longer text, like analysis documents, PR or CL descriptions, or documentation.OfficialWritingNo warnings★ 3.1K↓ —
- golden-rss-emptyyusufkaraaslan/Skill_SeekersUse when testing the empty rss golden buildTestingNo warnings★ 15.2K↓ —
- 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↓ —
- grill-with-docsflutter/agent-pluginsGrilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.OfficialTestingNo warnings★ 3.1K↓ —
- 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↓ —
- code-documentationflutter/agent-pluginsGuide for writing effective code documentation, including docstrings, JSDoc, dartdoc, and implementation comments. Use this skill when writing new code, adding features, or improving existing documentation in Dart, Python, or TypeScript to ensure clarity and maintainability.OfficialEngineeringNo warnings★ 3.1K↓ —
- idea-creatorwanshuiyin/Auto-claude-code-research-in-sleepGenerate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.ScienceNo warnings★ 18.1K↓ —
- golden-chat-emptyyusufkaraaslan/Skill_SeekersUse when testing the golden_chat_empty golden buildTestingNo warnings★ 15.2K↓ —
- 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↓ —
airunway-aks-setup
microsoft/skills
OfficialDevOpsUpdated 15 hours ago
From the author
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
Install
npx skills add microsoft/skills --skill airunway-aks-setup -a claude-code
Installs to .claude/skills/airunway-aks-setup/ · 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 (12)
- SKILL.md
- references/gpu-profiles.md
- references/model-sizing.md
- references/optional-gpu-day2.md
- references/powershell-notes.md
- references/steps/step-1-verify.md
- references/steps/step-2-controller.md
- references/steps/step-3-gpu.md
- references/steps/step-4-provider.md
- references/steps/step-5-deploy.md
- references/steps/step-6-summary.md
- references/troubleshooting.md