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 19 hours ago
45,604 skills
- cloud-monitoring-metric-selectiongoogle/skillsRetrieve, 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.OfficialDevOpsNo warnings★ 21.6K↓ —
- breakdown-epic-archgithub/awesome-copilotPrompt for creating the high-level technical architecture for an Epic, based on a Product Requirements Document.PlanningNo warnings★ 40.4K↓ —
- mmx-clisickn33/agentic-awesome-skillsUse mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax API resources from the terminal.EngineeringNo warnings★ 48.5K↓ —
- sql-code-reviewgithub/awesome-copilotUniversal SQL code review assistant that performs comprehensive security, maintainability, and code quality analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Focuses on SQL injection prevention, access control, code standards, and anti-pattern detection. Complements SQL optimization prompt for complete development coverage.DataNo 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↓ —
- gcp-gkesickn33/agentic-awesome-skillsDeploy and manage Google Kubernetes Engine clusters. Configure node pools, networking, and workload identity. Use when running Kubernetes on GCP.DevOpsNo warnings★ 48.5K↓ —
- 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↓ —
- azure-role-selectorgithub/awesome-copilotWhen user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.DevOpsNo warnings★ 40.4K↓ —
- 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↓ —
- jev-usesickn33/agentic-awesome-skillsRoute enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jev_judge and jev_gate MCP tools, batched into one call per state.OtherNo warnings★ 48.5K↓ —
- 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↓ —
- test-valuett-a1i/archifyImprove test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.TestingNo warnings★ 89K↓ —
- 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↓ —
- lemmalysickn33/agentic-awesome-skillsAlgorithm-first discipline: state Big-O, data structure, and algorithm family BEFORE writing loops, queries, or recursion. Catches O(n^2), N+1, and brute-force defaults.WritingNo warnings★ 48.5K↓ —
- centos-linux-triagegithub/awesome-copilotTriage and resolve CentOS issues using RHEL-compatible tooling, SELinux-aware practices, and firewalld.OtherNo warnings★ 40.4K↓ —
- lookdevsickn33/agentic-awesome-skillsHuman-in-the-loop web studio to tune AI-generated output by eye. Stand up a local interactive studio (sliders, pickers, drag handles) or an inline edit/highlight/comment annotation studio for prose & media, instead of guessing values or shipping a static comparison grid.WritingNo warnings★ 48.5K↓ —
- simplify-codebasett-a1i/archifySimplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any language; also use for 代码简化 or 熵回收. Do not use for general code review, onboarding, style-only refactoring, or performance tuning.DesignNo warnings★ 89K↓ —
- 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↓ —
- 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.MediaNo warnings★ 48.5K↓ —
- molykitsickn33/agentic-awesome-skillsCRITICAL: Use for MolyKit AI chat toolkit. Triggers on: BotClient, OpenAI, SSE streaming, AI chat, molykit, PlatformSend, spawn(), ThreadToken, cross-platform async, Chat widget, Messages, PromptInput, Avatar, LLMOtherNo warnings★ 48.5K↓ —
- pricingsickn33/agentic-awesome-skillsWhen the user wants help with pricing decisions, packaging, or monetization strategy.OtherNo warnings★ 48.5K↓ —
- radare2sickn33/agentic-awesome-skillsDrive the radare2 CLI for binary reconnaissance, disassembly, analysis, function locating, export, and lightweight patching (r2/rabin2/rasm2/radiff2) without a GUI.EngineeringNo warnings★ 48.5K↓ —
- qdrant-search-qualitygithub/awesome-copilotDiagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth.MarketingNo warnings★ 40.4K↓ —
- cloudishsickn33/agentic-awesome-skillsDeploy a Dockerfile, source folder, or existing image to Cloudish as a running container at a live URL, built server-side with no local Docker, with confirmation before spending credits.DevOpsNo warnings★ 48.5K↓ —
finnish-humanizer
github/awesome-copilot
WritingUpdated 2 days ago
From the author
Detect and remove AI-generated markers from Finnish text, making it sound like a native Finnish speaker wrote it. Use when asked to "humanize", "naturalize", or "remove AI feel" from Finnish text, or when editing .md/.txt files containing Finnish content. Identifies 26 patterns (12 Finnish-specific + 14 universal) and 4 style markers.
Install
npx skills add github/awesome-copilot --skill finnish-humanizer -a claude-code
Installs to .claude/skills/finnish-humanizer/ · 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 (2)
- SKILL.md
- references/patterns.md