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 11 hours ago
45,100 skills
- vast-gpuwanshuiyin/Auto-claude-code-research-in-sleepRent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.OtherNo warnings★ 18.1K↓ —
- flutter-add-widget-testflutter/agent-pluginsImplement a component-level test using `WidgetTester` to verify UI rendering and user interactions (tapping, scrolling, entering text). Use when validating that a specific widget displays correct data and responds to events as expected.OfficialTestingNo warnings★ 3.1K↓ —
- 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↓ —
- kill-argumentwanshuiyin/Auto-claude-code-research-in-sleepTwo-thread adversarial review: a fresh reviewer constructs the strongest 200-word rejection memo, then a second fresh reviewer defends the paper point-by-point and surfaces still-unresolved critical issues. Use when user says "kill argument", "adversarial review", "hostile review", "rebuttal preparation", "reviewer-2 simulation", or before submitting a theory paper that has already passed standard review rounds.ScienceNo warnings★ 18.1K↓ —
- embodiment-descriptionwanshuiyin/Auto-claude-code-research-in-sleepWrite detailed embodiment descriptions for patent specifications. Use when user says "撰写实施例", "write embodiment", "实施例描述", "detailed description", or wants to describe how to practice an invention.WritingNo warnings★ 18.1K↓ —Also in 1 other repo
- podmansickn33/agentic-awesome-skillsManage containers using Podman, the daemonless container engine.OtherNo warnings★ 48.5K↓ —
- 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↓ —
- prepare-releaseCherryHQ/cherry-studioPrepare a new release by collecting commits, generating bilingual release notes, updating version files, and creating a release branch. Use when asked to prepare/create a release, bump version, or run `/prepare-release`.ProductivityNo warnings★ 53K↓ —
- gh-stackCherryHQ/cherry-studioManage Cherry Studio stacked branches and pull requests with the GitHub gh-stack extension. Use for planning, creating, inspecting, rebasing, syncing, linking, or recovering a stack of dependent PRs.PlanningNo warnings★ 53K↓ —
- golden-chatyusufkaraaslan/Skill_SeekersUse when testing the golden_chat golden buildTestingNo warnings★ 15.2K↓ —
- golden-rssyusufkaraaslan/Skill_SeekersUse when testing the rss golden buildTestingNo warnings★ 15.2K↓ —
- creative-thinking-for-researchOrchestra-Research/AI-Research-SKILLsApplies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.ScienceNo warnings★ 14K↓ —Also in 1 other repo
- ara-rigor-reviewerOrchestra-Research/AI-Research-SKILLsPerforms ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject recommendation. Use after Level 1 structural validation passes, when an ARA needs an objective epistemic critique before publication or release.ScienceNo warnings★ 14K↓ —
- presenting-conference-talksOrchestra-Research/AI-Research-SKILLsGenerates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight presentations, or invited talks for ML and systems conferences.DocumentsNo warnings★ 14K↓ —
- knowledge-distillationOrchestra-Research/AI-Research-SKILLsCompress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.DevOpsNo warnings★ 14K↓ —
- ara-compilerOrchestra-Research/AI-Research-SKILLsCompiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.DocumentsNo warnings★ 14K↓ —
- sparse-autoencoder-trainingOrchestra-Research/AI-Research-SKILLsProvides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.OtherNo warnings★ 14K↓ —Also in 1 other repo
- pyvene-interventionsOrchestra-Research/AI-Research-SKILLsProvides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.TestingNo 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↓ —
- gitlab-cisickn33/agentic-awesome-skillsConfigure GitLab CI/CD pipelines and runners for automated building, testing, and deployment.TestingNo warnings★ 48.5K↓ —
- modal-serverless-gpuOrchestra-Research/AI-Research-SKILLsServerless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.DevOpsNo warnings★ 14K↓ —
- 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↓ —
- simpo-trainingOrchestra-Research/AI-Research-SKILLsSimple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.OtherNo warnings★ 14K↓ —
- golden-html-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationTestingNo warnings★ 15.2K↓ —
eas-app-stores
expo/skills
OfficialEngineeringUpdated 2 days ago
From the author
Build and submit iOS and Android apps with EAS to TestFlight, the App Store, or Google Play. Supports Expo and other React Native projects, plus existing native apps. Use for eas.json setup, release pipelines, signing, app versions and build numbers, store submissions, and listing metadata. For Expo websites and API routes, use eas-hosting; for adding React Native screens to a native app, use expo-brownfield.
Install
npx skills add expo/skills --skill eas-app-stores -a claude-code
Installs to .claude/skills/eas-app-stores/ · 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
Adoption55
Files (8)
- SKILL.md
- agents/openai.yaml
- references/app-store-metadata.md
- references/ios-app-store.md
- references/native-ios.md
- references/play-store.md
- references/testflight.md
- references/workflows.md