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.
39.063 de skill-uri din 1.798 de depozite · actualizat acum 13 minute
39.063 de skill-uri
- 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.AlteleFără avertismente★ 13,9 K↓ —
- wiki-enrichwanshuiyin/Auto-claude-code-research-in-sleepFill in the per-paper TODO sections of research-wiki/papers/<slug>.md pages that literature-ingest skills leave as bare scaffolds. Use when user says 'enrich wiki', 'fill paper TODOs', 'wiki body 補完', '把 paper 摘要寫進 wiki', 'research-wiki 自動填', or after a batch ingest that left papers/ as TODO scaffolds.ȘtiințăFără avertismente★ 18 K↓ —
- azure-advisormicrosoft/skillsUse Azure Advisor recommendations. WHEN: "show Advisor recommendations", "service retirements", "update recommendation status". DO NOT USE FOR: fixes or remediation (use azure-advisor-actionability).OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- golden-jupyter-kwyusufkaraaslan/Skill_SeekersUse when testing the golden_jupyter_kw golden buildTestareFără avertismente★ 15,2 K↓ —
- arxivwanshuiyin/Auto-claude-code-research-in-sleepSearch, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.ȘtiințăFără avertismente★ 18 K↓ —
- stripe-directorystripe/aiIdentifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request that requires selecting, finding, or engaging an external provider or organization — whether a specific one is named ("pay my Twilio bill"), implied ("donate to the Red Cross"), or only a category is stated ("set up a mailing client", "I need a database", "find me a CRM"). Directory supplies verified recipients and their documented payment or engagement path. Results are ranked by agent-readiness (how reliably an agent can complete the interaction), relevance and popularity. Don't treat this as a search-only tool. Examples: "setup a database", "find hosting", "pay X", "use Twilio", "donate $50 to the Red Cross", "book a table at Y", "subscribe to a CRM".OficialDateFără avertismente★ 2 K↓ —Apare și în 4 alte depozite
- aks-gpu-inferencemicrosoft/skillsDiagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- azure-communication-common-javamicrosoft/skillsAzure Communication Services common utilities for Java. Use when working with CommunicationTokenCredential, user identifiers, token refresh, or shared authentication across ACS services.OficialDevOpsFără avertismente★ 3,1 K↓ —
- 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.InginerieFără avertismente★ 13,9 K↓ —
- 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.TestareFără avertismente★ 19,1 K↓ —
- azure-speech-to-text-rest-pymicrosoft/skillsAzure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK. Triggers: "speech to text REST", "short audio transcription", "speech recognition REST API", "STT REST", "recognize speech REST". DO NOT USE FOR: Long audio (>60 seconds), real-time streaming, batch transcription, custom speech models, speech translation. Use Speech SDK or Batch Transcription API instead.OficialDevOpsFără avertismente★ 3,1 K↓ —
- azure-eventgrid-pymicrosoft/skillsAzure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures. Triggers: "event grid", "EventGridPublisherClient", "CloudEvent", "EventGridEvent", "publish events".OficialDevOpsFără avertismente★ 3,1 K↓ —
- customizemicrosoft/skillsInteractive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 3 alte depozite
- 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.DevOpsFără avertismente★ 13,9 K↓ —
- paper-planwanshuiyin/Auto-claude-code-research-in-sleepGenerate a structured paper outline from review conclusions and experiment results. Use when user says "写大纲", "paper outline", "plan the paper", "论文规划", or wants to create a paper plan before writing.ȘtiințăFără avertismente★ 18 K↓ —
- skillopt-sleepmicrosoft/SkillOptUse when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated CLAUDE.md/SKILL.md behind a held-out gate.InginerieFără avertismente★ 18,7 K↓ —
- golden-html-multiyusufkaraaslan/Skill_SeekersUse when testing the multi-file html buildTestareFără avertismente★ 15,2 K↓ —
- skillopt-sleepmicrosoft/SkillOptUse when the user wants Codex to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, wants Codex to review past sessions, learn preferences, consolidate memory/skills, run dry-run/run/adopt/status for SkillOpt-Sleep, or schedule background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated memory + skills behind a held-out gate.InginerieFără avertismente★ 18,7 K↓ —
- serverless-modalwanshuiyin/Auto-claude-code-research-in-sleepRun GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.DevOpsFără avertismente★ 18 K↓ —
- blip-2-vision-languageOrchestra-Research/AI-Research-SKILLsVision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.MediaFără avertismente★ 13,9 K↓ —
- constitutional-aiOrchestra-Research/AI-Research-SKILLsAnthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.AlteleFără avertismente★ 13,9 K↓ —
- azure-storage-blob-javamicrosoft/skillsBuild blob storage applications with Azure Storage Blob SDK for Java. Use when uploading, downloading, or managing files in Azure Blob Storage, working with containers, or implementing streaming data operations.OficialDevOpsFără avertismente★ 3,1 K↓ —
- azure-search-documents-dotnetmicrosoft/skillsAzure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET", "SearchClient", "SearchIndexClient", "vector search C#", "semantic search .NET", "hybrid search", "Azure.Search.Documents".OficialDevOpsFără avertismente★ 3,1 K↓ —
- azure-data-tables-javamicrosoft/skillsBuild table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.OficialDevOpsFără avertismente★ 3,1 K↓ —
azure-local-multi-rack
microsoft/skills
OficialDevOpsActualizat ieri
De la autor
Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.
Instalare
npx skills add microsoft/skills --skill azure-local-multi-rack -a claude-code
Se instalează în .claude/skills/azure-local-multi-rack/ · 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
Niciun avertisment.
De ce 93
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție56
Fișiere (9)
- SKILL.md
- references/cli-and-prereqs.md
- references/docs-map.md
- references/resource-types.md
- references/safety-rules.md
- workflows/networking/networking.md
- workflows/operate-and-monitor/operate-and-monitor.md
- workflows/plan-and-deploy/plan-and-deploy.md
- workflows/workload-management/workload-management.md