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 9 hours ago
45,100 skills
- 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
- azure-eventgrid-javamicrosoft/skillsBuild event-driven applications with Azure Event Grid SDK for Java. Use when publishing events, implementing pub/sub patterns, or integrating with Azure services via events.OfficialDevOpsNo warnings★ 3.1K↓ —
- ara-research-managerOrchestra-Research/AI-Research-SKILLsRecords research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.ScienceNo 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↓ —
- speculative-decodingOrchestra-Research/AI-Research-SKILLsAccelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.PlanningNo 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
- pytorch-lightningOrchestra-Research/AI-Research-SKILLsHigh-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.EngineeringNo warnings★ 14K↓ —
- azure-identity-pymicrosoft/skillsAzure Identity SDK for Python authentication with Microsoft Entra ID. Use for DefaultAzureCredential, managed identity, service principals, and token caching. Triggers: "azure-identity", "DefaultAzureCredential", "authentication", "managed identity", "service principal", "credential".OfficialDevOpsNo warnings★ 3.1K↓ —
- 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↓ —
- huggingface-tokenizersOrchestra-Research/AI-Research-SKILLsFast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.ScienceNo warnings★ 14K↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- new-relicsickn33/agentic-awesome-skillsConfigure New Relic observability platform for infrastructure and application monitoring.DevOpsNo warnings★ 48.5K↓ —
- expo-domexpo/skillsUse Expo DOM components to run web code in a webview on native and as-is on web. Migrate web code to native incrementally. For the end-to-end migration of a whole web app, use the expo-web-to-native skill.OfficialEngineeringNo warnings★ 3K↓ —
- nanogptOrchestra-Research/AI-Research-SKILLsEducational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).PlanningNo warnings★ 14K↓ —
- 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↓ —
- llama-factoryOrchestra-Research/AI-Research-SKILLsExpert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal supportEngineeringNo warnings★ 14K↓ —
- auto-paper-improvement-loopwanshuiyin/Auto-claude-code-research-in-sleepAutonomously improve a generated paper via GPT-6-Astra xhigh review → 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↓ —
- implementing-llms-litgptOrchestra-Research/AI-Research-SKILLsImplements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.PlanningNo warnings★ 14K↓ —
- evaluating-cosmos-policyOrchestra-Research/AI-Research-SKILLsEvaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.MediaNo warnings★ 14K↓ —
secops-cases
google/skills
OfficialSecurityUpdated 18 hours ago
From the author
Manage Google Security Operations (SecOps) SOAR cases throughout their lifecycle. Use when listing, creating, inspecting, updating, or closing SOAR cases; adding investigative comments and notes; updating case priority or description; or linking and grouping security alerts within cases. Supports both remote Google SecOps MCP tools and local fallback tools. Don't use for SIEM UDM searches or detection rule authoring.
Install
npx skills add google/skills --skill secops-cases -a claude-code
Installs to .claude/skills/secops-cases/ · 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: APACHE-2.0
Safety checks on SKILL.md
- Reads credential files such as ~/.ssh or ~/.awsLow
Why 93
Security95
Provenance100
Maintenance100
Licence100
Adoption67
Files (2)
- SKILL.md
- references/attribution.md