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 8 ore
45.602 skill-uri
- google-cloud-recipe-authgoogle/skillsProvides expert guidance on Identity and Access Management (IAM) and authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.OficialAlteleFără avertismente★ 21,6 K↓ —Apare și în 1 alt depozit
- 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↓ —
- 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↓ —
- 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↓ —
- pwn-chainsickn33/agentic-awesome-skillsGo from reverse engineering to a working exploit: stack/heap/kernel pwn workflows with pwntools, libc-database, ROP, and stabilization from CTF to authorized remote targets.DateFără avertismente★ 48,5 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↓ —
- fedora-linux-triagegithub/awesome-copilotTriage and resolve Fedora issues with dnf, systemd, and SELinux-aware guidance.AlteleFără 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↓ —
- seo-auditsickn33/agentic-awesome-skillsDiagnose and audit SEO issues affecting crawlability, indexation, rankings, and organic performance.MarketingFără 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↓ —
- consciousness-councilK-Dense-AI/scientific-agent-skillsStructures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges. Simulates thinking archetypes, separates evidence from assumptions and values, and synthesizes a conditional recommendation. Use when the user requests a council, panel, devil's advocate analysis, "mind council", or deliberate comparison of perspectives on a difficult choice.ȘtiințăFără avertismente★ 54,5 K↓ —
- benchling-integrationK-Dense-AI/scientific-agent-skillsBenchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.InginerieFără avertismente★ 54,5 K↓ —
- conventional-branchgithub/awesome-copilotCreate Git branches following the Conventional Branch specification (feature/, bugfix/, hotfix/, release/, chore/, plus AI agent prefixes ai/, copilot/, cursor/, claude/, codex/). Use when creating a new branch, naming a branch, or checking whether a branch name complies with the spec.PlanificareFără avertismente★ 40,4 K↓ —
- aws-ec2sickn33/agentic-awesome-skillsManage EC2 instances, AMIs, and auto-scaling groups. Configure security groups, key pairs, and instance types. Use when deploying compute resources on AWS.DevOpsFără avertismente★ 48,5 K↓ —
- google-mobile-ads-bannergoogle/skillsProvides instructions to implement, integrate, or configure Google Mobile Ads (GMA) banner ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up banner ads in a mobile application. Don't use for other ad formats like interstitial or rewarded ads.OficialMarketingFără avertismente★ 21,6 K↓ —
- genomic-intelligenceK-Dense-AI/scientific-agent-skillsPredicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.ȘtiințăFără avertismente★ 54,5 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↓ —
- google-cloud-storage-bucket-architectgoogle/skillsCreates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.OficialPlanificareFără avertismente★ 21,6 K↓ —
- google-cloud-recipe-foundation-buildergoogle/skillsDeploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills instead).OficialSecuritateFără avertismente★ 21,6 K↓ —
- gke-workload-scaling-troubleshootinggoogle/skillsDiagnoses GKE HorizontalPodAutoscaler (HPA) failures — metrics showing as <unknown>, FailedGetResourceMetric / FailedGetScale / FailedComputeMetricsReplicas events, missing Pod resource requests, custom/external metrics-pipeline breakage (FailedGetExternalMetric / FailedGetCustomMetric, unavailable metrics adapter, control-plane firewall blocking the adapter), HPA that won't scale up or down (tolerance / stabilization window / unavailable rate metrics), scale-to/from-zero problems, and slow HPA reaction on large clusters. Use when an HPA isn't scaling a workload as expected or reports metric errors. Don't use for configuring or authoring new HPA/VPA objects or scaling best practices (see the gke-workload-scaling skill), or for Cluster Autoscaler / node-pool sizing.OficialPlanificareFără avertismente★ 21,6 K↓ —
- ui-tokenssickn33/agentic-awesome-skillsView, add, or modify design tokens in the StyleSeed design systemDesignFără avertismente★ 48,5 K↓ —
- gke-ai-troubleshooting-tpu-mxla-hanggoogle/skillsDiagnose GKE Cloud TPU multi-slice training hangs (Megascale `HANG_DETECTED` logs and hang monitored events) using the ML Diagnostics `Megascale XLA (MXLA) Hang Analyzer` (`gcloud alpha mldiagnostics monitored-events`) and 1-minute Cloud Monitoring multi-slice latency metrics (`kubernetes.io/container/multislice/*`). Distinguishes XLA compiler/HLO launch divergence and host data-input stalls from TPU chip, SparseCore, ICI, or network fabric faults. Use when multi-slice TPU training jobs freeze without progressing steps, emit `HANG_DETECTED`, or stall in collective operations. Don't use for gradual step-time throughput drops without hangs (use gke-ai-troubleshooting-tpu-performance-degradation) or pod preemption/eviction restarts (use gke-ai-troubleshooting-jobset-interruption).OficialDevOpsFără avertismente★ 21,6 K↓ —
- google-cloud-networking-observabilitygoogle/skillsInvestigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.OficialDevOpsFără avertismente★ 21,6 K↓ —
- repo-standardizergithub/awesome-copilotPolish any GitHub repository's surface — labels (emoji rating tiers, P0–P3 priority, impact severity), issue forms, PR template, CI workflows, CODEOWNERS, rulesets, docs. Repo meta & config only — no code logic touched. Use when creating a new repo or polishing an existing one.InginerieFără avertismente★ 40,4 K↓ —
cloud-monitoring-metric-selection
google/skills
OficialDevOpsActualizat alaltăieri
De la autor
Retrieve, query, and identify relevant Cloud Monitoring metric descriptors on Google Cloud for a service or resource (such as Compute Engine, Spanner, BigQuery, Cloud Run, Cloud SQL, Pub/Sub, Cloud Storage, etc.). Use when asked to find, list, search, or discover GCP metric types, names, kind/value schemas, or descriptors.
Instalare
npx skills add google/skills --skill cloud-monitoring-metric-selection -a claude-code
Se instalează în .claude/skills/cloud-monitoring-metric-selection/ · 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: APACHE-2.0
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Fișiere (2)
- SKILL.md
- references/attribution.md