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.
49.404 skill-uri din 2.375 de depozite · actualizat acum 18 minute
49.404 skill-uri
- sozialdaten-sgbKlotzkette/claude-fuer-deutsches-rechtFür Sozialdaten im Datenschutzvorfall — SGB I und SGB X: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- genimlK-Dense-AI/scientific-agent-skillsSupports audited local Geniml genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- projektfinanzierungKlotzkette/claude-fuer-deutsches-rechtFür Projektfinanzierung Energie: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- onekgpdK-Dense-AI/scientific-agent-skillsQueries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which individuals are homozygous-reference at a position, which variants exist in the dataset or carried by specified individuals in a gene or region, the relatedness between two specified individuals. Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- context-statuspedrohcgs/claude-code-my-workflowShow current context status and session health. Use to check how much context has been used, whether auto-compact is approaching, and what state will be preserved.ProductivitateFără avertismente★ 1,7 K↓ —
- networkxsickn33/agentic-awesome-skillsNetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs.InginerieFără avertismente★ 49,1 K↓ —
- pr-squash-messagescenario-labs/skillsGenerate one short Conventional Commits squash message describing only the net diff between the PR's base and head, set its header as the PR title, validate it with the repository's commitlint and both copy its description to the clipboard and display it, when asked for a squash message. Works in any Scenario repository, whatever its default branch.AlteleFără avertismente★ 1,9 K↓ —
- openpivK-Dense-AI/scientific-agent-skillsPerforms Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.MediaFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- dsfa-erstellungKlotzkette/claude-fuer-deutsches-rechtFür DSFA – Datenschutz-Folgenabschätzung Art. 35 DSGVO: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- helm-chart-scaffoldingwshobson/agentsDesign, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.DevOpsFără avertismente★ 42,1 K↓ —
- arcgis-to-portaljsdatopian/portaljsMigrate a whole ArcGIS Hub site into a PortalJS Arc portal end-to-end. Harvests the Hub /data.json (DCAT-US) inventory, exports every FeatureService layer through the ArcGIS REST query API with resultOffset paging, converts each to the serverless dual tier (PMTiles render + GeoParquet query) with tabular items to Parquet, pushes everything to Cloudflare R2 via Git LFS, appends dual-tier datasets.json entries, and writes a source-vs-derived parity report. Use to move a City or sector ArcGIS Hub open-data portal onto PortalJS with no server-side compute.DevOpsFără avertismente★ 2,4 K↓ —
- ressort-bmjvKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMJV: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- pyhealthK-Dense-AI/scientific-agent-skillsBuilds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- arborK-Dense-AI/scientific-agent-skillsApplies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization. Uses persistent hypotheses, isolated experiments, evidence propagation and held-out candidate comparison for multi-experiment research runs. Includes a standard-library state manager and guidance for the RUC-NLPIR Arbor CLI.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- hivemind-graphactiveloopai/hivemindQuery the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).InginerieFără avertismente★ 1,6 K↓ —
- agent-platform-tuninggoogle/skillsAgent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).OficialDevOpsFără avertismente★ 21,8 K↓ —
- blucliLeoYeAI/agent-master-skillsBluOS CLI (blu) for discovery, playback, grouping, and volume.InginerieFără avertismente★ 2,2 K↓ —
- polarssickn33/agentic-awesome-skillsExpression-based DataFrame library for Python and Rust. Use for eager or lazy tabular analytics, ETL, and pandas migration; streaming support and memory needs depend on the query.DateFără avertismente★ 49,1 K↓ —
- cloud-logging-finopsgoogle/skillsAudits Cloud Logging costs for a Google Cloud project: the charges for log entries written to log buckets, the services, log streams and severities that drive them, and the log sinks that route them. Reconciles Cloud Billing export costs with Cloud Monitoring volume metrics, and generates a FinOps report with charts and copy-paste exclusion filters. Use when auditing Cloud Logging spend, finding logging waste, identifying top logging contributors, generating log cost reduction reports, or creating log sink exclusion filters. Don't use for querying log entries (use cloud-logging-query-generation), configuring Cloud Monitoring alerts, or querying metrics/traces.OficialRedactareFără avertismente★ 21,8 K↓ —
- 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.TestareFără avertismente★ 40,8 K↓ —
- pydeseq2K-Dense-AI/scientific-agent-skillsPerforms bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.TestareFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- richtlinien-entwurfKlotzkette/claude-fuer-deutsches-rechtFür Richtlinien Entwurf: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- improve-code-qualitywondelai/skillsGuided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says 'this works on my machine but I am scared to touch it'. For an aged codebase, remove-technical-debt; for greenfield structure, design-code-architecture; for a product and UX pass, improve-app; to optimize speed and structure, architecture-optimization. For one framework in isolation, invoke that skill directly.InginerieFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- pragmatic-programmerwondelai/skillsApply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.DesignFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
scenario-sparc3d
scenario-labs/skills
De la autor
Use when turning images or photos into 3D meshes with Sparc3D models on Scenario via MCP: single-image or multi-view image-to-3D, watertight meshes for game assets, AR/VR, or 3D printing, mesh-only versus PBR-textured output, face count targets, resolution tiers, or reconstructing human heads and busts with the Portrait variants. Keywords: Sparc3D 2.1 and 2.0, Hitem3D, image to 3D, img23d, multiview, watertight, PBR, GLB, OBJ, STL, FBX.
Instalare
npx skills add scenario-labs/skills --skill scenario-sparc3d -a claude-code
Se instalează în .claude/skills/scenario-sparc3d/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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