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 12 hours ago
45,602 skills
- microsoft-code-referencegithub/awesome-copilotLook up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs—to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.EngineeringNo warnings★ 40.4K↓ —
- acreadiness-assessgithub/awesome-copilotRun the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.MediaNo warnings★ 40.4K↓ —
- entra-agent-usergithub/awesome-copilotCreate Agent Users in Microsoft Entra ID from Agent Identities, enabling AI agents to act as digital workers with user identity capabilities in Microsoft 365 and Azure environments.DevOpsNo warnings★ 40.4K↓ —
- dotnet-upgradegithub/awesome-copilotReady-to-use prompts for comprehensive .NET framework upgrade analysis and executionOtherNo warnings★ 40.4K↓ —
- bgpt-paper-searchK-Dense-AI/scientific-agent-skillsSearches BGPT scientific papers by topic or DOI and retrieves claim-level evidence extracted from full text, including experiments, reported statistics, scope, limitations, and provenance. Use for literature reviews, evidence synthesis, and finding experimental details beyond abstracts.ScienceNo warnings★ 54.5K↓ —
- optimize-for-gpuK-Dense-AI/scientific-agent-skillsGPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.DataNo warnings★ 54.5K↓ —
- 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.EngineeringNo warnings★ 40.4K↓ —
- supabasesickn33/agentic-awesome-skillsUse when doing ANY task involving Supabase.ProductivityNo warnings★ 48.5K↓ —
- ginkgo-cloud-labK-Dense-AI/scientific-agent-skillsGuides protocol selection, input preparation, pricing checks, and browser ordering on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio). Applies to cell-free, E. coli, and Pichia protein expression; HiBiT, A280, and LabChip readouts; IVT mRNA/circRNA synthesis; thermal shift assays; Echo-MS methods; SPR target onboarding; plate-reader assay onboarding; and fluorescent pixel art.BrowserNo warnings★ 54.5K↓ —
- arize-experimentgithub/awesome-copilotCreates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.TestingNo warnings★ 40.4K↓ —
- fabric-lakehousegithub/awesome-copilotUse this skill to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.EngineeringNo warnings★ 40.4K↓ —
- cellxgene-censusK-Dense-AI/scientific-agent-skillsQueries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.ProductivityNo warnings★ 54.5K↓ —
- prdgithub/awesome-copilotGenerate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.PlanningNo warnings★ 40.4K↓ —Also in 2 other repos
- workshop-creategithub/awesome-copilotCreate a new workshop or use an existing directory as one. Handles two paths: (A) use an existing local directory the operator points at, or (B) create a new private GitHub repo in the signed-in account. Never creates a repo inside another repo.OtherNo warnings★ 40.4K↓ —
- 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.DataNo warnings★ 54.5K↓ —
- analyticssickn33/agentic-awesome-skillsWhen the user wants to set up, improve, or audit analytics tracking and measurement.DataNo warnings★ 48.5K↓ —
- breakdown-epic-pmgithub/awesome-copilotPrompt for creating an Epic Product Requirements Document (PRD) for a new epic. This PRD will be used as input for generating a technical architecture specification.PlanningNo warnings★ 40.4K↓ —
- audit-logsickn33/agentic-awesome-skillsAudit trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.OtherNo warnings★ 48.5K↓ —
- macos-golden-gate-designgithub/awesome-copilotDesign, implement, review, or refactor native macOS 27 Golden Gate interfaces in SwiftUI or AppKit. Use when a Mac app must match Apple's current macOS 27 UI kit and restrained Liquid Glass language: integrated windows, full-height sidebars, native toolbars, flat lists, tables, and forms, clear pane boundaries, accessible materials, and removal of unnecessary nested cards, framed panels, or glassmorphism. Also use for Figma macOS 27 design-to-code work and audits of interfaces that feel too boxed.DesignNo warnings★ 40.4K↓ —
- azure-akssickn33/agentic-awesome-skillsDeploy and manage Azure Kubernetes Service clusters. Configure node pools, networking, and integrations. Use when running Kubernetes workloads on Azure.DevOpsNo warnings★ 48.5K↓ —
- shuffle-json-datagithub/awesome-copilotShuffle repetitive JSON objects safely by validating schema consistency before randomising entries.OtherNo warnings★ 40.4K↓ —
- hf-clisickn33/agentic-awesome-skillsCurated upstream guidance for Hf Cli; use when the workflow matches the user goal.EngineeringNo warnings★ 48.5K↓ —
- 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.DataNo warnings★ 54.5K↓ —
- agent-supply-chaingithub/awesome-copilotVerify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"OtherNo warnings★ 40.4K↓ —
webly
sickn33/agentic-awesome-skills
NewWritingUpdated yesterday
From the author
Publish a website or share files at a live URL in seconds with no account, then let the person claim it, edit it over Webly's MCP server, and publish drafts they approve.
Install
npx skills add sickn33/agentic-awesome-skills --skill webly -a claude-code
Installs to .claude/skills/webly/ · 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: APACHE-2.0
Safety checks on SKILL.md
No warnings.
Why 95
Security100
Provenance95
Maintenance100
Licence100
Adoption72
Files (3)
- LICENSE
- SKILL.md
- references/mcp-and-domains.md