Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
48.620 de skill-uri din 2.355 de depozite · actualizat acum 3 minute
48.620 de skill-uri
- gaming-agbKlotzkette/claude-fuer-deutsches-rechtFür Gaming AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- inso-plKlotzkette/claude-fuer-deutsches-rechtFür Mandantenkommunikation: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Insolvenzrecht.AlteleFără avertismente★ 1,8 K↓ —
- klageKlotzkette/claude-fuer-deutsches-rechtFür Klage: Mandantenkommunikation und Entscheidungsvorlage: erstellt Entwurf mit Antrag, Beweis und Anlagen; Ergebnis: Schriftsatz mit Begründungs- und Anlagenlogik.AlteleFără avertismente★ 1,8 K↓ —
- aws-penetration-testingzebbern/claude-code-guideThis skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.TestareFără avertismente★ 4,7 K↓ —
- preisangabenKlotzkette/claude-fuer-deutsches-rechtFür Preisangaben (PAngV 2022): ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- build-evidence-mapgithub/awesome-copilotBuild an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision. Use when Copilot must preserve supporting, contradicting, qualifying, and missing evidence with exact source regions instead of collapsing disagreement into prose.ȘtiințăFără avertismente★ 40,7 K↓ —
- mahnbescheidKlotzkette/claude-fuer-deutsches-rechtFür Mahnverfahren – Paragrafen 688 ff. ZPO: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- bmlehKlotzkette/claude-fuer-deutsches-rechtFür Legistik-Werkstatt — Allgemein: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- musik-app-beiKlotzkette/claude-fuer-deutsches-rechtFür Datenbankrecht für Musik-, Film- und Bildarchive — Mediendatenbanken: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- widerspruch-interessenKlotzkette/claude-fuer-deutsches-rechtFür Widerspruch: Mehrparteienkonflikt und Interessenmatrix: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- agent-master-skillsActualizatLeoYeAI/agent-master-skillsA curated collection of 2803+ best agent skills — AI tools, productivity, marketing, frontend, mobile, backend, DevOps and more. Harness-agnostic, refreshed daily by MyClaw.ai — Powered by MyClaw.aiDevOpsFără avertismente★ 2,2 K↓ —
- find-hypertable-candidatestimescale/pg-aiguideUse this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.DateFără avertismente★ 1,9 K↓ —
- researchwriteYuan1z0825/nature-skillsCompose, revise, or audit research proposals, opening reports, and research plans from supporting evidence. Use for 研究计划、开题报告、科研项目申请书. Invoked as researchwrite for compatibility; use nature-writing for general manuscript sections.ȘtiințăFără avertismente★ 51,7 K↓ —
- dev-debugcodeaholicguy/ai-devkitAI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).InginerieFără avertismente★ 1,7 K↓ —
- nature-academic-searchYuan1z0825/nature-skillsSearch literature across sources, verify or manage citations, and build MeSH strategies or citation-impact audits. Use for 文献检索、引文核对、参考文献管理、严格他引 and evidence-backed citer profiles; not for translating a paper or drafting manuscript prose.ȘtiințăFără avertismente★ 51,7 K↓ —
- nature-readerYuan1z0825/nature-skillsCreate source-grounded Chinese-English paper readers with aligned text, figures, tables, and equations. Use for 全文翻译、中英文对照、论文精读 or source-linked questions about a paper; respect a requested excerpt or question without generating a full reader.ȘtiințăFără avertismente★ 51,7 K↓ —
- engage-sdk-integrationandroid/skillsHelps developers integrate, debug, and resolve Play Engage SDK implementation issues. Use when adding Engage SDK support, generating publishing code, mapping data classes to entities, or fixing SDK-related errors.OficialInginerieFără avertismente★ 10,2 K↓ —
- tddcodeaholicguy/ai-devkitAI DevKit · Test-driven development — write a failing test before writing production code. Use when implementing new functionality, adding behavior, or fixing bugs during active development.TestareFără avertismente★ 1,7 K↓ —
- 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.ȘtiințăFără avertismente★ 55,6 K↓ —
- skill-nameReScienceLab/opc-skillsClear description of what this skill does and when to use it. Include trigger keywords and contexts inline, e.g. "Use when user wants to X, Y, or Z."AlteleFără avertismente★ 1,9 K↓ —
- founder-competitorsJakeschincariol/founder-skillMaps every competitor and the gap they leave. Finds the direct competitors, indirect ones and the substitutes a buyer would use instead, from public sources only, and records what each sells, at what price, how they position themselves and what their customers complain about in public reviews, every fact with a link. Ends with a positioning map and the gap the new business can own. Use when the user says "who are my competitors", "is this market crowded", "what else is out there", "competitor analysis", "find the gap", or "who am I up against".AlteleFără avertismente★ 2,3 K↓ —
- founder-launchJakeschincariol/founder-skillYour launch lead. Builds a dated, step-by-step launch plan: a cheap real-world test first (a waitlist, a pre-sale or a pop-up with a real price, so real buyers confirm what the simulated panel said), then the countdown to opening day with owners and deadlines, the launch-day run sheet, and the first 30 days of what to measure and what to change. Use when the user says "how do I launch", "launch plan", "when can I open", "launch checklist", "go live", or "soft open".TestareFără avertismente★ 2,3 K↓ —
- founder-offerJakeschincariol/founder-skillBuilds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.TestareFără avertismente★ 2,3 K↓ —
- founder-boardJakeschincariol/founder-skillYour board of directors. Puts a business idea in front of a three-member board, each a sub-agent reading the idea through one published framework: the Offers lens (from Alex Hormozi's $100M Offers), the Monopoly lens (from Peter Thiel's Zero to One) and the Product lens (from Walter Isaacson's biography of Steve Jobs). Each member scores the idea, names the risks that would kill it and votes fund, fund with conditions, or pass. Use when the user says "test my business idea", "would this work", "pressure-test this", "what would a board say", "is this a good business", or starts the founder pack on a new idea.TestareFără avertismente★ 2,3 K↓ —
histolab
K-Dense-AI/scientific-agent-skills
DocumenteActualizat acum 6 zile
De la autor
Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset preparation. For multiplexed imaging or deep learning inference pipelines, use pathml.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill histolab -a claude-code
Se instalează în .claude/skills/histolab/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: Personalizată sau neclară
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De ce 89
Securitate100
Proveniență95
Întreținere100
Licență45
Adopție73
Fișiere (8)
- SKILL.md
- references/core_capabilities.md
- references/filters_preprocessing.md
- references/slide_management.md
- references/tile_extraction.md
- references/tissue_masks.md
- references/typical_workflows.md
- references/visualization.md