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.
49,450 skills from 2,407 repositories · updated 28 minutes ago
49,450 skills
- api-design-principleswshobson/agentsMaster REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.DesignNo warnings★ 42.2K↓ —
- ressort-bmzKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMZ: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- hundred-million-offerswondelai/skillsCreate irresistible offers using the Value Equation, bonus stacking, risk-reversing guarantees, and ethical scarcity. Use when the user mentions "grand slam offer", "make my offer more compelling", "what bonuses should I add", "guarantee strategy", "offer naming", or "people say its too expensive". Also trigger when packaging a product for higher perceived value, justifying premium pricing instead of discounting, designing a money-back guarantee, or structuring tiers to maximize conversions. Covers the MAGIC naming formula and starving-crowd targeting. For product positioning, see obviously-awesome. For outbound sales, see predictable-revenue.OtherNo warnings★ 2.6K↓ —Also in 2 other repos
- hivemind-goalsactiveloopai/hivemindCreate, track, and read team goals via Hivemind from openclaw. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.EngineeringNo warnings★ 1.6K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanningNo warnings★ 1.6K↓ —
- scenario-ad-variantsscenario-labs/skillsUse when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Also for revising one variant or resuming a partially completed batch. Not for a new commercial from a still image, ordinary single-clip grading, or automatic Cartesian combinations.MarketingNo warnings★ 2.8K↓ —
- understand-domainEgonex-AI/Understand-AnythingExtract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.OtherNo warnings★ 90.9K↓ —
- seabornsickn33/agentic-awesome-skillsSeaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.EngineeringNo warnings★ 49.2K↓ —
- scenario-meshyscenario-labs/skillsUse when creating or refining 3D assets with Meshy models on Scenario via MCP: image-to-3D from one photo or 1-4 multi-view angles, text-to-3D, retexturing an existing GLB, remeshing to a target polycount, UV unwrapping, auto-rigging a humanoid character, or applying a library animation clip. Keywords: Meshy 7 and Meshy 6, Ultra mode, Smart Topology, PBR maps, texture prompt, triangle or quad topology, game-ready mesh, A-pose, T-pose, GLB pipeline.MediaNo warnings★ 2.8K↓ —
- steve-jobs-design-reviewwondelai/skillsReview designs, products, and features with Steve Jobs' standards: ruthless simplicity, focus, and end-to-end excellence. Use when the user mentions "Steve Jobs review", "design review", "product review", "what would Steve do", "insanely great", "this feels too complicated", "too many features", "product taste", "saying no", or "is this good enough to ship". Also trigger when critiquing a UI, feature, or roadmap for focus and simplicity, cutting scope to the essential, or pressure-testing the whole experience from first run to daily use. Covers the simplicity audit, the no list, design-is-how-it-works, end-to-end ownership, demo culture, and a Jobs-style review protocol with binary verdicts. For visual design fundamentals, see refactoring-ui. For usability audits, see ux-heuristics. For detail polish, see microinteractions.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- smbcrm-advanced-toolsLeoYeAI/agent-master-skillsUse when helping SMBcrm customers with Private Integration Tokens, REST API v2, workflows, custom webhooks, MCP, or Agent Studio API. Use for API troubleshooting, automation design, data sync, AI assistant setup, or any task involving https://services.smbcrm.com endpoints.DesignNo warnings★ 2.2K↓ —
- false-friendsKlotzkette/claude-fuer-deutsches-rechtFür Mandantenkommunikation: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Common-Law-Kompass für deutsche Wirtschaftsjuristen.LegalNo warnings★ 1.8K↓ —
- redteam-qualitygateKlotzkette/claude-fuer-deutsches-rechtFür Patentrecht Red Team: prüft Ergebnis, Beweislast und Gegenposition; Ergebnis: Gegenprüfung mit Beweis- und Fristencheck.OtherNo warnings★ 1.8K↓ —
- hey-lolLeoYeAI/agent-master-skillsBecome an AI creator on hey.lol - a social platform where AI agents earn money by posting content and engaging with humans.OtherNo warnings★ 2.2K↓ —
- understand-knowledgeEgonex-AI/Understand-AnythingAnalyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.OtherNo warnings★ 90.9K↓ —
- scientific-schematicsK-Dense-AI/scientific-agent-skillsGenerates scientific diagram drafts using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.7 Flash for quality review. Refines when the review requests improvement, with at most two generations. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.ScienceNo warnings★ 56.2K↓ —
- scenario-reportscenario-labs/skillsUse when a Scenario user wants to report a bug or request a change, on the public tracker at github.com/scenario-labs/skills or by email to [email protected]: turning a failed generation, MCP tool error, or unclear skill into a reproducible report, collecting trace ids with diagnostics_run, stripping keys, signed asset URLs, and personal data, asking before sharing a team or project id, or building a prefilled issue URL. Keywords: file an issue, feature request, feedback.ProductivityNo warnings★ 2.8K↓ —
- blog-schemaAgriciDaniel/claude-blogGenerate JSON-LD for ONE blog post (BlogPosting with Person, Organization, BreadcrumbList, ImageObject, VideoObject; FAQPage only as optional entity markup) in a single @graph, and check it against Google's current structured data support. Use when the user says "generate schema", "json-ld for this post", "blog schema". Not for auditing schema across a whole site or other schema types (claude-seo seo-schema), not for product pages, and not a promise of rich results: FAQ rich results ended 2026-05-07.WritingNo warnings★ 2.7K↓ —
- portaljs-check-data-qualitydatopian/portaljsAudit a local or remote tabular file (CSV/TSV) for common data quality issues — schema, nulls, types, duplicates. Read-only. Use when a dataset needs a quality check before publishing, or a showcase renders wrong (blank cells, garbled numbers, an unsortable date column) and the cause needs isolating.DataNo warnings★ 2.4K↓ —
- open-source-sbomKlotzkette/claude-fuer-deutsches-rechtFür Open Source und SBOM: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: robotik-recht. Route: open-source-sbom.OtherNo warnings★ 1.8K↓ —
- scenarioscenario-labs/skillsUse when connecting an AI agent to Scenario (scenario.com) through MCP, or when a task involves generating images, video, 3D, audio, sprites, textures, or game assets. Also when picking a Scenario model, running a LoRA, refining a generation prompt, uploading reference images, waiting on generation jobs, checking credits or quota, hitting Scenario auth, scope, or Forbidden errors, or setting up mcp.scenario.com in Claude Code, Cursor, VSCode, or another agent.MediaNo warnings★ 2.8K↓ —
- liteparseK-Dense-AI/scientific-agent-skillsLocal document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.DocumentsNo warnings★ 56.2K↓ —Also in 1 other repo
- dbt-sf-to-bq-translatorgoogle/skillsTranslates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to BigQuery on Google Cloud. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.OfficialDataNo warnings★ 22.2K↓ —
- eval-driven-devgithub/awesome-copilotImprove AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.TestingNo warnings★ 40.8K↓ —
prompt-engineering-patterns
wshobson/agents
DesignUpdated 1 hour ago
From the author
This skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot prompting", or wants to apply advanced prompt engineering patterns for production LLM applications.
Install
npx skills add wshobson/agents --skill prompt-engineering-patterns -a claude-code
Installs to .claude/skills/prompt-engineering-patterns/ · 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
Runs bundled scriptsNo network use seenLicence: MIT
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Security85
Provenance95
Maintenance100
Licence100
Adoption71
Files (10)
- SKILL.md
- assets/few-shot-examples.json
- assets/prompt-template-library.md
- references/chain-of-thought.md
- references/details.md
- references/few-shot-learning.md
- references/prompt-optimization.md
- references/prompt-templates.md
- references/system-prompts.md
- scripts/optimize-prompt.py