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.
45.604 skill-uri din 2.205 depozite · actualizat acum 14 ore
45.602 skill-uri
- sveltekitsickn33/agentic-awesome-skillsBuild full-stack web applications with SvelteKit — file-based routing, SSR, SSG, API routes, and form actions in one framework.InginerieFără avertismente★ 48,5 K↓ —
- gem-devops-guidelinesgithub/awesome-copilotDesign or review infrastructure, deployment, CI/CD, Docker, Kubernetes, health checks, rollback, feature flags, production readiness, and mobile release workflows. Use for DevOps, platform, container, pipeline, or release tasks.DevOpsFără avertismente★ 40,4 K↓ —
- google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skillsDiscovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).OficialDateFără avertismente★ 21,6 K↓ —
- tokenwisesickn33/agentic-awesome-skillsMeasurement-driven model router for Claude Code. Routes Haiku/Sonnet/Opus per task class, logs every routed task with real $ numbers, and A/B tests cheaper tiers before you trust the savings.TestareFără avertismente★ 48,5 K↓ —
- ui-motionsickn33/agentic-awesome-skillsApply a named StyleSeed motion to a component — either one of the 5 personality seeds (Spring/Silk/Snap/Float/Pulse × entrance/exit/hover/press/layout) or a distinctive keyword move from the motion library (toggle-flip, toggle-curtain, reveal-blur, pop-in, shimmer, …).DesignFără avertismente★ 48,5 K↓ —
- torch-geometricK-Dense-AI/scientific-agent-skillsSupports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX analytics or non-graph PyTorch models.DateFără avertismente★ 54,5 K↓ —
- roundup-setupgithub/awesome-copilotInteractive onboarding that learns your communication style, audiences, and data sources to configure personalized status briefings. Paste in examples of updates you already write, answer a few questions, and roundup calibrates itself to your workflow.RedactareFără avertismente★ 40,4 K↓ —
- upstash-redisgithub/awesome-copilotUse Redis over HTTP from serverless and edge runtimes with @upstash/redis, and add rate limiting with @upstash/ratelimit. Use when the user mentions Upstash Redis, needs Redis from a Next.js route handler or middleware, Vercel, Cloudflare Workers, Deno, or Bun without TCP connection pooling, or wants cache-aside with TTLs, a session store, counters, or a 429 rate limiter using fixed window, sliding window, or token bucket. DO NOT use for self-hosted or TCP Redis clients (ioredis, node-redis), Redis Cluster administration, or vector similarity search.DevOpsFără avertismente★ 40,4 K↓ —
- ui-tokenssickn33/agentic-awesome-skillsView, add, or modify design tokens in the StyleSeed design systemDesignFără avertismente★ 48,5 K↓ —
- google-cloud-solution-agentic-ai-data-science-workflowgoogle/skillsDesigns a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.OficialDateFără avertismente★ 21,6 K↓ —
- database-lookupK-Dense-AI/scientific-agent-skillsQueries documented public database APIs with explicit endpoints, filters, pagination, and provenance. Used when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.DateFără avertismente★ 54,5 K↓ —
- gke-ai-troubleshooting-node-unresponsive-timeoutgoogle/skillsDiagnose and mitigate GKE TPU or GPU nodes stuck in NotReady / NodeStatusUnknown ("Kubelet stopped posting node status") due to host kernel panics, hardware lockups, or disabled node auto-repair. Use when nodes stop heartbeating beyond the node auto-repair threshold and pods remain stuck in Terminating. Don't use for healthy nodes, pod-only application crashes, or routine GKE upgrades.OficialAlteleFără avertismente★ 21,6 K↓ —
- krexasickn33/agentic-awesome-skillsTurn a trading idea, post or video into fixed rules, backtest and paper-trade them, and request a user-approved live agent through Krexa's MCP server. Cannot move funds.MediaFără avertismente★ 48,5 K↓ —
- gke-ai-troubleshooting-handle-disruption-gpu-tpugoogle/skillsDiagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, network policy configuration, or non-disruption workload deployment.OficialDevOpsFără avertismente★ 21,6 K↓ —
- gke-ai-troubleshooting-tpu-performance-degradationgoogle/skillsDiagnose GKE Cloud TPU training throughput drops and step-time regressions (15%+ TPU duty-cycle drop) using ML Diagnostics Workload Monitoring (`gcloud alpha mldiagnostics monitored-events` / `hypercomputecluster.googleapis.com/v1alpha`) and 1-minute Cloud Monitoring system metrics (`kubernetes.io/node/accelerator/*`). Distinguishes hardware and network fabric throttling from workload resource bottlenecks (HBM capacity, host memory, or host CPU saturation). Use when TPU training throughput or duty cycle drops without crashing pods, when `PERFORMANCE_DEGRADATION` monitored events fire, or when triaging slow multi-slice training steps. Don't use for complete multi-slice XLA execution stalls with `HANG_DETECTED` logs (use gke-ai-troubleshooting-tpu-mxla-hang) or pod eviction/interruption restarts (use gke-ai-troubleshooting-jobset-interruption).OficialDevOpsFără avertismente★ 21,6 K↓ —
- wiki-yylosickn33/agentic-awesome-skillsUse YYLO Ledger wiki Records as durable project knowledge. Search before creating, classify information correctly, and make revision-safe Markdown updates without editing Ledger storage directly.RedactareFără avertismente★ 48,5 K↓ —
- wordpresssickn33/agentic-awesome-skillsWordPress development workflow covering theme development, plugin creation, WooCommerce integration, performance optimization, and security hardening. Includes WordPress 7.0 features: Real-Time Collaboration, AI Connectors, Abilities API, DataViews, and PHP-only blocks.SecuritateFără avertismente★ 48,5 K↓ —
- conventional-commitgithub/awesome-copilotPrompt and workflow for generating conventional commit messages using a structured XML format. Guides users to create standardized, descriptive commit messages in line with the Conventional Commits specification, including instructions, examples, and validation.InginerieFără avertismente★ 40,4 K↓ —
- google-cloud-solution-hybrid-search-alloydbgoogle/skillsDiscovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.OficialDevOpsFără avertismente★ 21,6 K↓ —
- ai-productsickn33/agentic-awesome-skillsDesign and evaluate LLM product features, retrieval, validated outputs, latency, and cost controls.DesignFără avertismente★ 48,5 K↓ —
- anti-sleepsickn33/agentic-awesome-skillsKeep a Mac awake with caffeinate during long builds, downloads, or supervised automation runs.AlteleFără avertismente★ 48,5 K↓ —
- desk-journalgithub/awesome-copilotWrite, append, or read desk journal entries. The journal is persistent memory — what survives session boundaries. A good entry has: what was done, current state, next step.RedactareFără avertismente★ 40,4 K↓ —
- google-cloud-solution-guided-gke-ai-migrationgoogle/skillsGuides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.OficialDevOpsFără avertismente★ 21,6 K↓ —
- google-cloud-solution-rag-enterprise-search-gke-sqldbgoogle/skillsDiscovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.OficialDevOpsFără avertismente★ 21,6 K↓ —
openapi-spec-generation
wshobson/agents
PlanificareActualizat alaltăieri
De la autor
Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.
Instalare
npx skills add wshobson/agents --skill openapi-spec-generation -a claude-code
Se instalează în .claude/skills/openapi-spec-generation/ · 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 95
Securitate100
Proveniență95
Întreținere100
Licență100
Adopție71
Fișiere (3)
- SKILL.md
- references/code-first-and-tooling.md
- references/details.md