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.
35.001 skill-uri din 1.572 de depozite · actualizat acum 6 minute
34.999 de skill-uri
- polars-bioK-Dense-AI/scientific-agent-skillsPerforms genomic interval overlap, nearest, merge, coverage, complement and subtraction on Polars DataFrames, and reads or writes BED, VCF, BCF, BAM, CRAM, GFF, GTF, FASTA and FASTQ data. Use for coordinate-aware genomic joins, read-depth analysis, lazy bioinformatics I/O, SQL queries or migration from bioframe.DateFără avertismente★ 54,4 K↓ —
- hunt-ldapsickn33/agentic-awesome-skillsHunt LDAP Injection and XPath InjectionAlteleFără avertismente★ 48,4 K↓ —
- cockneysickn33/agentic-awesome-skillsCheeky Cockney coding mode: terse replies, the smallest correct change, plain English for anything risky.InginerieFără avertismente★ 48,4 K↓ —
- google-cloud-solution-agentic-ai-bidirectional-streaminggoogle/skillsGuides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.OficialDesignFără avertismente★ 21,5 K↓ —
- google-cloud-solution-agentic-ai-borderless-data-lakehousegoogle/skillsDiscovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).OficialDevOpsFără avertismente★ 21,5 K↓ —
- remembergithub/awesome-copilotTransforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `/remember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.ProductivitateFără avertismente★ 40,4 K↓ —
- declarative-agentsgithub/awesome-copilotComplete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integrationAlteleFără avertismente★ 40,4 K↓ —
- research-grantsK-Dense-AI/scientific-agent-skillsSupports research proposal preparation and review for NSF, NIH, DOE, DARPA, and Taiwan NSTC, including opportunity-specific requirements, aims, review criteria, budgets, broader impacts, forms, and resubmissions. Use for investigator-authored grant development, compliance matrices, and proposal critiques.ȘtiințăFără avertismente★ 54,4 K↓ —
- gtm-developer-ecosystemgithub/awesome-copilotBuild and scale developer-led adoption through ecosystem programs. Use when deciding open vs curated ecosystems, building developer programs, scaling platform adoption, or designing student program pipelines.AlteleFără avertismente★ 40,4 K↓ —
- eval-harness-firstwshobson/agentsBuild the evaluation harness that gates every fine-tuning run — golden sets, per-failure-mode graders, judge calibration, and base-model baselines. Use when starting a fine-tuning effort, when converting traces into an eval set, or when calibrating a judge against human labels.AlteleFără avertismente★ 41,6 K↓ —
- yes-mdsickn33/agentic-awesome-skills6-layer AI governance: safety gates, evidence-based debugging, anti-slack detection, and machine-enforced hooks. Makes AI safe, thorough, and honest.InginerieFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- ot-icssickn33/agentic-awesome-skillsAuthorized OT/ICS security assessment: Purdue-model zoning review, PLC/SCADA exposure, industrial protocol discovery, and passive-first evaluation discipline.SecuritateFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- powerbi-modelinggithub/awesome-copilotPower BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.DesignFără avertismente★ 40,4 K↓ —
- tamarindK-Dense-AI/scientific-agent-skillsProvides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.DesignFără avertismente★ 54,4 K↓ —Apare și în 1 alt depozit
- dhdna-profilerK-Dense-AI/scientific-agent-skillsApplies the DHDNA framework as an exploratory rubric for reasoning and writing patterns in supplied text. Used for explicit requests for DHDNA, cognitive-style reflection, a thinking-pattern profile, or comparisons of textual reasoning. Scores describe evidence in the sample, not validated psychological traits or personal identity.RedactareFără avertismente★ 54,4 K↓ —
- mcp-cligithub/awesome-copilotInterface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers, list available MCP servers/tools, or call MCP tools from command line.InginerieFără avertismente★ 40,4 K↓ —
- social-publishingwshobson/agentsSchedule and publish social media posts across 13 platforms (X, LinkedIn, Instagram, Facebook Pages, TikTok, Discord, Telegram, YouTube, Reddit, WordPress, Pinterest) via the SocialClaw API. Use when the user wants to publish, schedule, or manage social media content programmatically. Requires SOCIALCLAW_API_KEY.MarketingFără avertismente★ 41,6 K↓ —
- plotlysickn33/agentic-awesome-skillsInteractive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.ȘtiințăFără avertismente★ 48,4 K↓ —
- gdb-clisickn33/agentic-awesome-skillsGDB debugging assistant for AI agents - analyze core dumps, debug live processes, investigate crashes and deadlocks with source code correlationInginerieFără avertismente★ 48,4 K↓ —Apare și în 1 alt depozit
- nextflowK-Dense-AI/scientific-agent-skillsBuilds, runs, and debugs Nextflow DSL2 pipelines and nf-core workflows. Use for Nextflow, nf-core, .nf files, nextflow.config, processes/channels/operators, samplesheets, nf-test, modules/subworkflows, container and executor configuration, HPC/SLURM or cloud deployment, and failed or resumed pipeline runs.TestareFără avertismente★ 54,4 K↓ —Apare și în 1 alt depozit
- glassersickn33/agentic-awesome-skillsSearch, inspect, and run third-party data APIs through one CLI when the environment has no suitable integration.InginerieFără avertismente★ 48,4 K↓ —
- datalineage-summarygoogle/skillsSummarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).OficialProductivitateFără avertismente★ 21,5 K↓ —
- spark-optimizationwshobson/agentsOptimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.InginerieFără avertismente★ 41,6 K↓ —
- gitlab-ci-patternswshobson/agentsBuild GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.TestareFără avertismente★ 41,6 K↓ —
meeting-minutes
github/awesome-copilot
De la autor
Generate concise, actionable meeting minutes for internal meetings. Includes metadata, attendees, agenda, decisions, action items (owner + due date), and follow-up steps.
Instalare
npx skills add github/awesome-copilot --skill meeting-minutes -a claude-code
Se instalează în .claude/skills/meeting-minutes/ · 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.
La ce are acces
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- SKILL.md