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 2 hours ago
49,492 skills
- agent-platform-inferencegoogle/skillsConnects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.OfficialTestingNo warnings★ 21.9K↓ —
- restore-credentialsandroid/skillsProvides knowledge and workflows to implement Android's Restore Credentials feature using the androidx.credentials library. Use this skill to create, sign in with, and delete restore keys, enabling silent user sign-in on new devices after a restore. It covers version compatibility, dependencies, server-side prerequisites, and the complete client-side implementation for creating, retrieving, and clearing restore keys.OfficialOtherNo warnings★ 10.3K↓ —
- ai-legal-opsKlotzkette/claude-fuer-deutsches-rechtFür digitale Werkzeuge und Legal Ops in der Kanzlei: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.LegalNo warnings★ 1.8K↓ —
- blogAgriciDaniel/claude-blogFull-lifecycle blog engine with 31 sub-skills, 12 templates, 100-point scoring, and 5 agents. Routes requests to the right sub-skill: writing, rewriting, analysis, outlines, audits, schema, charts, images, repurposing, AI citation SEO, FLOW prompts, topic clusters, and multilingual publishing. Optimized for Google rankings, E-E-A-T, and AI citations. Supports any platform. Use when the user asks to create, revise, analyze, plan, translate, localize, audit, or repurpose blog content, or invokes a /blog subcommand. Do not activate merely because the word "blog" appears in an unrelated coding, theme-debugging, database, log-analysis, or definition request.WritingNo warnings★ 2.6K↓ —
- mitarbeiterKlotzkette/claude-fuer-deutsches-rechtFür Mitarbeiter: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Berufsrecht Anwälte.OtherNo warnings★ 1.8K↓ —
- memorycodeaholicguy/ai-devkitAI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.ProductivityNo warnings★ 1.7K↓ —
- oil-uiUpdatedoil-oil/oil-ui设计、改进和评审网站、App、后台与组件的界面：探索设计方向、生成多风格同屏对比页，并基于真实截图打磨视觉层级；按请求交付对比页、设计说明、设计稿或可运行界面。只负责设计判断，不用于纯业务逻辑、接口构建、无界面变化的代码整理，或改法已完全明确的日常修改（如改文案、调数量、删指定元素、复用现有样式，哪怕带有“优化”字样）。已安装 oil-ui-pro 时交给 oil-ui-pro。DesignNo warnings★ 2.7K↓ —
- opcodeLeoYeAI/agent-master-skillsZero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.ProductivityNo warnings★ 2.2K↓ —
- archifytt-a1i/archifyCreate validated architecture, workflow, sequence, data-flow, lifecycle/state, ERD, class, tree, timeline, and waterfall diagrams as explorable standalone HTML with dark/light themes, motion and image/SVG/WebM export. Accept requirements or Mermaid; inspect repository evidence for code-backed diagrams. Use when visualizing systems, API calls, pipelines, schemas, histories, timings, or everyday steps, parts, relationships and states. Also turn an answer into a one-page explainer, with the conclusion first, structured panels, native diagrams and charts, when the user asks for a page, an explainer or an answer to share (做成一页, 用页面讲), or proactively when the user's rules opt in with an [archify explainer: ...] line. Not for dashboards.MediaNo warnings★ 93.3K↓ —
- treasury-and-liquiditycbrock84/headcountManages cash and liquidity — cash forecasting, runway, working capital, banking structure, and currency and counterparty exposure. Use this to build a cash forecast, extend runway, improve working capital, decide where cash should sit, or assess exposure to a bank, currency, or customer concentration.OtherNo warnings★ 2.6K↓ —
- portaljs-new-portaldatopian/portaljsScaffold a new PortalJS data portal from a brief. Copies the canonical template from examples/portaljs-catalog and substitutes project tokens. Use when starting a brand-new data portal project from scratch.OtherNo warnings★ 2.4K↓ —
- grant-proposalpedrohcgs/claude-code-my-workflowScaffold a research grant proposal (NSF, NIH, ERC, or foundation) by composing existing primitives — pulls identification strategy from an `/interview-me` spec, delegates the data-management plan to `/data-management-plan` and the facilities statement to `/capture-environment`, and emits a funder-requirements checklist. Use when user says "draft a grant", "write a proposal", "NSF proposal", "NIH aims", "ERC application", "foundation grant", "specific aims", or "scaffold a grant proposal". NOT a submission tool — produces a draft the user uploads to the sponsor's portal themselves.ScienceNo warnings★ 1.7K↓ —
- astropysickn33/agentic-awesome-skillsAstropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.DataNo warnings★ 49.1K↓ —
- ai-ml-governancecbrock84/headcountGoverns models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.DevOpsNo warnings★ 2.6K↓ —
- chief-financial-officercbrock84/headcountAn agent organization structured as a company — 15+ departments, 125+ skills, each independently installable, citing the standards and regulators that settle the question. Runs in Claude Code and ChatGPT.FinanceNo warnings★ 2.6K↓ —
- canteraK-Dense-AI/scientific-agent-skillsRuns Cantera homogeneous chemical reactors and evaluates ignition delay with mechanism provenance, conservation checks, and numerical refinement. Use for combustion kinetics, closed adiabatic ideal-gas constant-volume or constant-pressure ignition, temperature histories, or mechanism-specific ignition-delay comparisons.ScienceNo warnings★ 56.1K↓ —Also in 2 other repos
- behavioral-marketingcbrock84/headcountApplies decision science and cognitive bias research to marketing and product decisions — how people actually choose under uncertainty, and how framing, defaults, sequencing, and social context change behavior. Use this to diagnose why a well-argued offer is not converting, to structure choices and pricing presentation, to design an experience around how attention and memory work, or to pressure-test whether a persuasion tactic is legitimate or manipulative.MarketingNo warnings★ 2.6K↓ —
- expo-uisickn33/agentic-awesome-skillsBuild native UI with the @expo/ui package: real SwiftUI on iOS and Jetpack Compose on Android rendered from React in an Expo or React Native app.DesignNo warnings★ 49.1K↓ —
- portaljs-add-datasetdatopian/portaljsAdd a dataset (CSV, TSV, JSON, or GeoJSON) to an existing PortalJS portal. Appends an entry to datasets.json so the catalog and showcase render it automatically; routes the data by source (local file vs remote URL) — R2 via Git LFS by default, remote URLs by passthrough. Use when registering a new dataset in a scaffolded portal.DataNo warnings★ 2.4K↓ —
- flowkitK-Dense-AI/scientific-agent-skillsAnalyzes flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces. Use for reproducible gate counts, population percentages, gated fluorescence summaries, or reproducing a FlowJo analysis in Python. For FCS metadata inspection or file-format repair alone, use FlowIO.EngineeringNo warnings★ 56.1K↓ —Also in 2 other repos
- datamolK-Dense-AI/scientific-agent-skillsPythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.DesignNo warnings★ 56.1K↓ —Also in 2 other repos
- data-governancecbrock84/headcountEstablishes ownership, definitions, quality, access, and lineage for the organization's data. Use this when metrics disagree between teams, when nobody knows which dataset is authoritative, when setting up data ownership or access policy, when data quality is unreliable, or before opening a dataset to a wider audience.OtherNo warnings★ 2.6K↓ —
- product-requirementscbrock84/headcountWrites down what is being built so a team can build it and know when they are done — problem and success measure before solution, scope stated by exclusion, user-visible behavior including the states everyone forgets, acceptance criteria someone can test, and the open questions named rather than buried. Use this to write a specification, review one that is causing rework, or work out why a delivered feature technically matched the request and still was not what anyone wanted.PlanningNo warnings★ 2.6K↓ —
- outbound-prospectingcbrock84/headcountFinds, qualifies, and reaches prospects through cold outreach — list building, qualification criteria, cold email and multi-channel sequences, and the follow-up that actually gets replies. Use this to build a prospect list, write cold outreach, fix a sequence that is not getting responses, define qualification criteria, or decide whether a segment is worth pursuing.WritingNo warnings★ 2.6K↓ —
torchdrug
K-Dense-AI/scientific-agent-skills
ScienceUpdated 3 days ago
From the author
Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill torchdrug -a claude-code
Installs to .claude/skills/torchdrug/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (Custom or unclear) does not let us redistribute its files. The install commands fetch them from GitHub instead.
What it can touch
Instructions onlyUses the networkLicence: Custom or unclear
Safety checks on SKILL.md
No warnings.
Why 89
Security100
Provenance95
Maintenance100
Licence45
Adoption73
Files (10)
- SKILL.md
- references/core_concepts.md
- references/datasets.md
- references/knowledge_graphs.md
- references/models_architectures.md
- references/molecular_generation.md
- references/molecular_property_prediction.md
- references/protein_modeling.md
- references/retrosynthesis.md
- references/review.md