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.
45,604 skills from 2,205 repositories · updated 10 hours ago
45,602 skills
- folklore-variant-evidenceK-Dense-AI/scientific-agent-skillsRetrieves ClinGen gene-disease validity assertions for a public gene or disease, and reviews source-linked public evidence and literature for one supported GRCh38 germline nuclear SNV or simple indel through Folklore Clinical Variant Interpretation MCP. Used when a scientific agent must branch deterministically on resolved, ambiguous, not-found, invalid, unsupported, or unavailable variant outcomes; chain a resolved public variant into related literature or publication details; or preserve evidence provenance without accepting patient, phenotype, family, segregation, or private case data.ScienceNo warnings★ 54.5K↓ —
- debian-linux-triagegithub/awesome-copilotTriage and resolve Debian Linux issues with apt, systemd, and AppArmor-aware guidance.OtherNo warnings★ 40.4K↓ —
- 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).OfficialDataNo warnings★ 21.6K↓ —
- postgresql-code-reviewgithub/awesome-copilotPostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).DataNo warnings★ 40.4K↓ —Also in 1 other repo
- harness-engineeringgithub/awesome-copilotAdopt repository-level harness engineering for coding agents. Use when a user wants to prevent repeated AI coding-agent mistakes by turning failures into durable instructions, drift checks, regression tests, failure memory, and adoption reports tailored to the target repository.TestingNo warnings★ 40.4K↓ —
- 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.OfficialDevOpsNo warnings★ 21.6K↓ —
- 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.OfficialOtherNo warnings★ 21.6K↓ —
- markdown-mermaid-writingK-Dense-AI/scientific-agent-skillsWrites scientific Markdown documentation and Mermaid diagrams for workflows, relationships, timelines, and schemas. Provides syntax references, document templates, accessibility guidance, and version-aware rendering checks. Use when a user requests Markdown, Mermaid, or a text-based structural diagram; quantitative scientific figures require suitable plotting tools.WritingNo warnings★ 54.5K↓ —
- 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).OfficialDevOpsNo warnings★ 21.6K↓ —
- 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.OfficialDevOpsNo warnings★ 21.6K↓ —
- google-mobile-ads-android-migrate-to-next-gengoogle/skillsMigrates Android applications from the old, legacy Google Mobile Ads (GMA) SDK (com.google.android.gms:play-services-ads) to the new GMA Next-Gen SDK (com.google.android.libraries.ads.mobile.sdk:ads-mobile-sdk). Provides comprehensive mapping tables for imports, classes, and method signatures to help determine migration steps. Use when migrating an existing Android codebase from the old, legacy GMA SDK to GMA Next-Gen SDK.OfficialMarketingNo warnings★ 21.6K↓ —
- 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.OfficialDevOpsNo warnings★ 21.6K↓ —
- documentation-writergithub/awesome-copilotDiátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.WritingNo warnings★ 40.4K↓ —
- 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.OfficialDevOpsNo warnings★ 21.6K↓ —
- google-cloud-solution-agentic-ai-borderless-data-lakehousegoogle/skillsDiscovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).OfficialDevOpsNo warnings★ 21.6K↓ —
- cloud-logging-cross-project-configurationgoogle/skillsConfigure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations.OfficialOtherNo warnings★ 21.6K↓ —
- devops-rollout-plangithub/awesome-copilotGenerate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changesDevOpsNo warnings★ 40.4K↓ —
- google-cloud-recipe-onboardinggoogle/skillsGuides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.OfficialDevOpsNo warnings★ 21.6K↓ —Also in 1 other repo
- bug-reproduction-briefgithub/awesome-copilotTurn a vague, intermittent, or environment-specific bug report into a minimal evidence-backed reproduction before proposing a fix.PlanningNo warnings★ 40.4K↓ —
- 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.ScienceNo warnings★ 54.5K↓ —
- csharp-docsgithub/awesome-copilotEnsure that C# types are documented with XML comments and follow best practices for documentation.OtherNo warnings★ 40.4K↓ —
- 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.EngineeringNo warnings★ 54.5K↓ —
- 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.EngineeringNo warnings★ 40.4K↓ —
- 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).OfficialDevOpsNo warnings★ 21.6K↓ —
ad-campaign-analyzer
github/awesome-copilot
MarketingUpdated 2 days ago
From the author
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
Install
npx skills add github/awesome-copilot --skill ad-campaign-analyzer -a claude-code
Installs to .claude/skills/ad-campaign-analyzer/ · 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: MIT
Safety checks on SKILL.md
No warnings.
Why 95
Security100
Provenance95
Maintenance100
Licence100
Adoption71
Files (1)
- SKILL.md