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
- 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↓ —
- block-no-verify-hookwshobson/agentsConfigure a PreToolUse hook to prevent AI agents from skipping git pre-commit hooks with --no-verify and other bypass flags. Use when setting up Claude Code projects that enforce commit quality gates.EngineeringNo warnings★ 41.7K↓ —
- podmansickn33/agentic-awesome-skillsManage containers using Podman, the daemonless container engine.OtherNo warnings★ 48.5K↓ —
- golden-jupyteryusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter golden buildTestingNo warnings★ 15.2K↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- moe-trainingOrchestra-Research/AI-Research-SKILLsTrain Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.PlanningNo 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↓ —
- golden-pptx-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumentsNo warnings★ 15.2K↓ —
- model-mergingOrchestra-Research/AI-Research-SKILLsMerge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.DevOpsNo warnings★ 14K↓ —
- model-pruningOrchestra-Research/AI-Research-SKILLsReduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.OtherNo warnings★ 14K↓ —
- 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↓ —
- nemo-guardrailsOrchestra-Research/AI-Research-SKILLsNVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.OtherNo warnings★ 14K↓ —
- claims-draftingwanshuiyin/Auto-claude-code-research-in-sleepDraft patent claims for an invention. Use when user says "撰写权利要求", "draft claims", "写权利要求书", "claim drafting", or wants to create patent claims. The core skill of the patent pipeline.OtherNo warnings★ 18.1K↓ —
- golden-wordyusufkaraaslan/Skill_SeekersUse when testing the word golden buildTestingNo warnings★ 15.2K↓ —
- golden-man-kwyusufkaraaslan/Skill_SeekersUse when testing the man golden buildTestingNo warnings★ 15.2K↓ —
- golden-chatyusufkaraaslan/Skill_SeekersUse when testing the golden_chat golden buildTestingNo warnings★ 15.2K↓ —
- golden-epubyusufkaraaslan/Skill_SeekersUse when testing the epub golden buildTestingNo warnings★ 15.2K↓ —
- golden-htmlyusufkaraaslan/Skill_SeekersUse when testing the html golden buildTestingNo warnings★ 15.2K↓ —
- ego-lite-simplifycitrolabs/ego-liteFind and implement evidence-backed simplifications in the ego-lite repository. Use when reviewing the codebase for dead code, duplicated state or APIs, speculative abstractions, unnecessary compatibility layers, hand-written infrastructure, excessive tests or documentation, or when the user asks to reduce code size or maintenance complexity without hiding behavior changes.TestingNo warnings★ 19.7K↓ —
- golden-pdf-kwyusufkaraaslan/Skill_SeekersUse when testing keyword categorizationDocumentsNo warnings★ 15.2K↓ —
training-llms-megatron
Orchestra-Research/AI-Research-SKILLs
From the author
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.
Install
npx skills add Orchestra-Research/AI-Research-SKILLs --skill training-llms-megatron -a claude-code
Installs to .claude/skills/training-llms-megatron/ · 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.
What it can touch
Safety checks on SKILL.md
No warnings.
Why 93
Files (5)
- SKILL.md
- references/benchmarks.md
- references/parallelism-guide.md
- references/production-examples.md
- references/training-recipes.md