Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
36.065 de skill-uri din 1.636 de depozite · actualizat acum 17 minute
36.065 de skill-uri
- find-skillsCherryHQ/cherry-studioFind and install agent skills when the user asks for a capability that may already exist as a skill.AlteleFără avertismente★ 52,9 K↓ —
- gh-create-prCherryHQ/cherry-studioCreate or update GitHub pull requests using the repository-required workflow and template compliance. Use when asked to create/open/update a PR so the assistant reads `.github/pull_request_template.md`, fills every template section, preserves markdown structure exactly, and marks missing data as N/A or None instead of skipping sections.JuridicFără avertismente★ 52,9 K↓ —
- llamaguardOrchestra-Research/AI-Research-SKILLsMeta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.DevOpsFără avertismente★ 13,9 K↓ —
- create-skillCherryHQ/cherry-studioCreate a new skill in the current repository. Use when the user wants to create/add a new skill, or mentions creating a skill from scratch. This skill follows the workflow defined in .agents/skills/README.md and helps scaffold, validate, and sync new skills.ProductivitateFără avertismente★ 52,9 K↓ —
- agent-notesCherryHQ/cherry-studioUse when deciding whether a Cherry Studio change needs an Agent Note, authoring or reviewing a Spec, recording a durable bug-fix decision, moving a note between proposed/implemented/rejected, or checking supersession and stacked Spec approval.ProductivitateFără avertismente★ 52,9 K↓ —
- 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.PlanificareFără avertismente★ 52,9 K↓ —
- experiment-auditwanshuiyin/Auto-claude-code-research-in-sleepAudit experiment integrity before claiming results. Uses fresh-agent GPT-6-Astra review (same-family provisional in the base Codex mirror) to check for fake ground truth, score normalization fraud, phantom results, and insufficient scope. Use when user says "审计实验", "check experiment integrity", "audit results", "实验诚实度", or after experiments complete before writing claims.RedactareFără avertismente★ 18 K↓ —
- segment-anything-modelOrchestra-Research/AI-Research-SKILLsFoundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.MediaFără avertismente★ 13,9 K↓ —
- azure-ai-contentsafety-pymicrosoft/skillsAzure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification. Triggers: "azure-ai-contentsafety", "ContentSafetyClient", "content moderation", "harmful content", "text analysis", "image analysis".OficialDevOpsFără avertismente★ 3,1 K↓ —
- azure-ai-anomalydetector-javamicrosoft/skillsBuild anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.OficialDevOpsFără avertismente★ 3,1 K↓ —
- 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 supportInginerieFără avertismente★ 13,9 K↓ —
- 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.MediaFără avertismente★ 13,9 K↓ —
- 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.PlanificareFără avertismente★ 13,9 K↓ —
- 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.ProductivitateFără avertismente★ 13,9 K↓ —
- sglangOrchestra-Research/AI-Research-SKILLsFast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.MarketingFără avertismente★ 13,9 K↓ —
- torchforge-rl-trainingOrchestra-Research/AI-Research-SKILLsProvides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. Use when you want clean RL abstractions, easy algorithm experimentation, or scalable training with Monarch and TorchTitan.AlteleFără avertismente★ 13,9 K↓ —
- 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.DevOpsFără avertismente★ 13,9 K↓ —
- rwkv-architectureOrchestra-Research/AI-Research-SKILLsRNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.PlanificareFără avertismente★ 13,9 K↓ —
- dspyOrchestra-Research/AI-Research-SKILLsBuild complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programmingAlteleFără avertismente★ 13,9 K↓ —
- fine-tuning-openvla-oftOrchestra-Research/AI-Research-SKILLsFine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVLA-OFT paper results, training custom VLA action heads (L1 or diffusion), deploying server-client inference for ALOHA, or debugging normalization, LoRA merge, and cross-GPU issues.DevOpsFără avertismente★ 13,9 K↓ —
- langsmith-observabilityOrchestra-Research/AI-Research-SKILLsLLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.DevOpsFără avertismente★ 13,9 K↓ —
- 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.PlanificareFără avertismente★ 13,9 K↓ —
- serving-llms-vllmOrchestra-Research/AI-Research-SKILLsServes LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.DevOpsFără avertismente★ 13,9 K↓ —
- qzcliwanshuiyin/Auto-claude-code-research-in-sleepManage GPU compute jobs on the Qizhi (启智) platform using qzcli — a kubectl-style CLI tool. Use when user says "qzcli", "启智平台", "submit job", "stop job", "查计算组", "avail", "list jobs", "batch submit", or needs to manage distributed training jobs on a Qizhi instance.InginerieFără avertismente★ 18 K↓ —Apare și în 1 alt depozit
expo-migrate-module
expo/skills
OficialJuridicActualizat ieri
De la autor
Migrate an existing Apple/Swift Expo native module from the Expo Modules API 1.0 definition DSL to the 2.0 macro API (sometimes called v2) while preserving its JavaScript and TypeScript contract. Use when converting or incrementally adopting @ExpoModule, @JS, @Event, @SharedObject, or @Record in an existing module. Do not use for creating a new module, general Expo SDK upgrades, or Android/Kotlin migrations.
Instalare
npx skills add expo/skills --skill expo-migrate-module -a claude-code
Se instalează în .claude/skills/expo-migrate-module/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
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De ce 93
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție55
Fișiere (5)
- SKILL.md
- agents/openai.yaml
- references/compatibility.md
- references/example.md
- references/migration-map.md