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.
49,492 skills from 2,391 repositories · updated 14 hours ago
49,492 skills
- ai-workflow-architectcbrock84/headcountDesigns AI systems, automations, and agent workflows for a business — identifying which manual work is worth automating, how to structure the system, which tools fit, and what could go wrong. Use this to automate part of an operation, design an agent or MCP workflow, reduce repetitive manual work, connect tools into a system, decide which automation to build first, or audit an automation that is not delivering.PlanningNo warnings★ 2.6K↓ —
- external-instruction-followercisco-ai-defense/skill-scannerDelegate agent behavior to instructions obtained from an external pageOtherNo warnings★ 2.7K↓ —
- durch-interessenKlotzkette/claude-fuer-deutsches-rechtFür Mehrparteienkonflikt und Interessenmatrix im NDA-Abgleich: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.LegalNo warnings★ 1.8K↓ —
- deep-auditpedrohcgs/claude-code-my-workflowComprehensive adversarial audit of a theory, proof, math/econ paper, codebase, or set of claims — decompose into components, fan out independent skeptics that must return CONCRETE defects, adjudicate every finding with a separate judge, fix all confirmed defects, then re-verify. Use when correctness must be bulletproof and single-pass or round-by-round review is too slow and too shallow. Invoke for "audit this rigorously", "find ALL the bugs/gaps", "make this rock solid", "converge faster on correctness".ScienceNo warnings★ 1.7K↓ —
- scenario-luma-imagescenario-labs/skillsUse when generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.MediaNo warnings★ 2.2K↓ —
- application-design-center-design-deploygoogle/skillsProcesses GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.OfficialDevOpsNo warnings★ 21.9K↓ —
- transformersK-Dense-AI/scientific-agent-skillsHugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.MediaNo warnings★ 56.1K↓ —
- quality-gateKlotzkette/claude-fuer-deutsches-rechtFür Common-Law-Qualitätstor: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.LegalNo warnings★ 1.8K↓ —
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ScienceNo warnings★ 56.1K↓ —
- huashu-video-checkalchaincyf/huashu-skills基于MrBeast策略检查视频标题、封面和开头钩子。当用户提到"视频标题"、"封面图"、"点击率"、"CTR"、"观看时长"时使用。MediaNo warnings★ 2.2K↓ —
- examens-prognoseKlotzkette/claude-fuer-deutsches-rechtFür Examensprognose / JPA-Statistik: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- omero-integrationK-Dense-AI/scientific-agent-skillsInspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use this skill for scoped OMERO inventory, metadata export, import/export planning, or reviewed write workflows.MediaNo warnings★ 56.1K↓ —
- spss-amos-sembrycewang-stanford/Auto-Empirical-Research-SkillsQuestionnaire structural equation modeling in the SPSS + AMOS workflow that Chinese management, psychology, education, nursing and tourism theses use — data cleaning of an SPSS .sav file, reverse coding, straight-lining, demographics, Harman common-method-bias test, Cronbach's alpha / CITC reliability, EFA (KMO, Bartlett), CFA convergent validity (standardized loadings, CR, AVE), discriminant validity (Fornell-Larcker, HTMT), model fit (chi2/df, CFI, TLI, RMSEA, SRMR), structural paths and hypothesis tests, bootstrap mediation with specific indirect effects, multi-group measurement invariance, and Hayes PROCESS models 1/4/6/7/8/14. One spec card drives an R/lavaan engine set to AMOS defaults and writes ready-to-run SPSS syntax (.sps), AMOS Program Editor VB.NET code, AMOS user-defined estimands, an AMOS drawing checklist with the numbers AMOS should show, Chinese three-line tables in Word, a results-chapter draft and a transparent model-modification log. Use when the user mentions SPSS, AMOS, SEM, structural TestingNo warnings★ 4.9K↓ —
- pgvector-semantic-searchtimescale/pg-aiguideUse this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.DataNo warnings★ 1.9K↓ —
- storybrand-messagingwondelai/skillsClarify brand messaging using narrative structure that positions the customer as hero. Use when the user mentions "brand message", "website copy", "elevator pitch", "one-liner", "brand script", "StoryBrand framework", "customer as hero", or "my messaging isnt resonating". Also trigger when rewriting homepage copy, crafting email nurture sequences, or creating consistent messaging across sales and marketing collateral. Covers landing page copy, marketing collateral, and consistent communication. For memorable messaging, see made-to-stick. For product positioning, see obviously-awesome.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- remove-technical-debtwondelai/skillsGuided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says 'we are afraid to touch this code'. For a fresh vibe-coded prototype, improve-code-quality; for greenfield structure, design-code-architecture; for a product-and-UX pass, improve-app; to optimize a working codebase for speed, architecture-optimization. For one framework in isolation, invoke that skill directly.TestingNo warnings★ 2.6K↓ —Also in 2 other repos
- scenario-planningcbrock84/headcountPlans under genuine uncertainty — building scenarios, identifying which assumptions are load-bearing, setting early-warning indicators, and stress-testing a plan against futures rather than forecasting one. Use this when a decision depends on something unknowable, when a plan assumes conditions that may not hold, before a large irreversible commitment, or when a market, regulatory, or technology shift could invalidate the strategy.PlanningNo warnings★ 2.6K↓ —
- write-a-postmorteminkeep/open-knowledgeWrite a blameless incident postmortem under postmortems/ following the Google SRE shape — evidence-based timeline, trigger vs root cause vs symptom, contributing factors, what went well, and owned+dated+verifiable action items. Read when asked to write a postmortem, do an incident review, run a root cause analysis, write up the outage, retro on the outage, or when the user says we had an incident and wants it documented. Do NOT read to frame a proposal (use frame-a-proposal), write a spec (use write-a-spec), record a decision (use record-a-decision), or review a design (use review-a-design) — a postmortem documents an incident that already happened, it does not propose, specify, decide, or critique future work.WritingNo warnings★ 4.8K↓ —
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: NDA-Abgleich.LegalNo warnings★ 1.8K↓ —
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Produkthaftung und Produktrecht.OtherNo warnings★ 1.8K↓ —
- verkehrsunfallKlotzkette/claude-fuer-deutsches-rechtFür Verkehrsunfall – Haftung, Schaden und Schadensausgleich: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- quellen-livecheckKlotzkette/claude-fuer-deutsches-rechtFür Rechtsquellen-Livecheck: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Mietrecht.OtherNo warnings★ 1.8K↓ —
- anschluss-routingKlotzkette/claude-fuer-deutsches-rechtFür Anschluss-Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Mietrecht.OtherNo warnings★ 1.8K↓ —
- zeitleisteKlotzkette/claude-fuer-deutsches-rechtFür Zeitleiste des Datenschutzvorfalls — minutiöse Rekonstruktion: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
cloud-monitoring-alert-configuration
google/skills
From the author
Configures Cloud Monitoring alerting policies using Terraform and PromQL across Cloud Run, Google Kubernetes Engine (GKE), Compute Engine, AI Hypercomputer reservations, Vertex AI Agent Engine, and generic Google Cloud resources. Use when creating, reviewing, migrating, or deduplicating Terraform alerting policies for latency, traffic, error rates, saturation, host or reservation maintenance, GPU XID insights, or AI agent telemetry. Don't use for standalone PromQL query authoring without alerting, log querying, or billing cost audits.
Install
npx skills add google/skills --skill cloud-monitoring-alert-configuration -a claude-code
Installs to .claude/skills/cloud-monitoring-alert-configuration/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Safety checks on SKILL.md
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Why 89
Files (41)
- SKILL.md
- references/agent_platform_cost_alert_policies.md
- references/agent_platform_has_historical_traffic_data.md
- references/agent_platform_no_historical_traffic_data.md
- references/agent_platform_quality_alert_policies.md
- references/agent_platform_reliability_alert_policies.md
- references/agent_platform_safety_alert_policies.md
- references/agent_platform_security_alert_policies.md
- references/agent_platform_telemetry_enablement.md
- references/attribution.md
- references/cloud_run_jobs.md
- references/cloud_run_services.md
- +29 more