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.
6.040 de skill-uri din 156 de depozite · actualizat acum 8 minute
147 de skill-uri
- weaviatesickn33/agentic-awesome-skillsSearch, query, inspect, create, and import data into Weaviate vector database collections using official scripts and references.DateFără avertismente★ 48,2 K↓ —
- daskK-Dense-AI/scientific-agent-skillsScales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.DateFără avertismente★ 53,4 K↓ —
- polarsK-Dense-AI/scientific-agent-skillsHigh-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.DateFără avertismente★ 53,4 K↓ —
- cloud-databases-onboardinggoogle/skillsGuides users through discovering their database requirements, recommends a Google Cloud database based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?', 'Help me pick a database', or when a user wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or database migrations.OficialDateFără avertismente★ 21,5 K↓ —
- seabornK-Dense-AI/scientific-agent-skillsCreates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.DateFără avertismente★ 53,4 K↓ —
- astropyK-Dense-AI/scientific-agent-skillsCore Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.DateFără avertismente★ 53,4 K↓ —
- chaingptinternet-court/internet-court-skillBuild with the ChainGPT Web3 AI developer platform. Full API/SDK reference and project scaffolding for: Web3 AI Chatbot & LLM, AI NFT Generator, Smart Contract Generator, Smart Contract Auditor, AI Crypto News, AgenticOS Twitter agents, and Solidity LLM. Use when building blockchain apps, Web3 chatbots, NFT tools, smart contract tools, crypto news feeds, AI agents, or integrating any ChainGPT API. Triggers: chaingpt, web3 ai, nft generator, smart contract audit, crypto news api, agenticos, solidity llm, cgpt, blockchain ai, token analytics.DateFără avertismente★ 6,8 K↓ —
- polarssickn33/agentic-awesome-skillsFast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.DateFără avertismente★ 48,2 K↓ —
- astropysickn33/agentic-awesome-skillsAstropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.DateFără avertismente★ 48,2 K↓ —
- fullstack-devMiniMax-AI/skillsFull-stack backend architecture and frontend-backend integration guide. TRIGGER when: building a full-stack app, creating REST API with frontend, scaffolding backend service, building todo app, building CRUD app, building real-time app, building chat app, Express + React, Next.js API, Node.js backend, Python backend, Go backend, designing service layers, implementing error handling, managing config/auth, setting up API clients, implementing auth flows, handling file uploads, adding real-time features (SSE/WebSocket), hardening for production. DO NOT TRIGGER when: pure frontend UI work, pure CSS/styling, database schema only.OficialDateFără avertismente★ 13,7 K↓ —
- citation-crosscheckwanshuiyin/Auto-claude-code-research-in-sleepConditionally double-blind bibliographic cross-check (double-blind only when the host can isolate the web agent; a flag-only heuristic when isolation can't be attested): one agent extracts each cited entry verbatim from the local .bib, a second independently re-fetches the same paper's record from the web while blind to the .bib, and a third extractor emits a mechanical field-by-field delta to catch dropped/re-ordered authors, wrong years, wrong venues, and bad DOIs/arXiv ids. The main agent (never a shard) assigns the MATCH/MINOR/MISMATCH verdict per reference, and exports a side-by-side spreadsheet. Use when user says "citation crosscheck", "double-blind citation check", "verify bib against scholar", "bib field audit", "引用交叉核对", or before submission when bibliography FIELD accuracy (not just existence) must be certified.DateFără avertismente★ 17,8 K↓ —
- citation-crosscheckwanshuiyin/Auto-claude-code-research-in-sleepDouble-blind bibliographic cross-check: one agent extracts each cited entry verbatim from the local .bib, a second independently re-fetches the same paper's record from the web while blind to the .bib, and a third extractor emits a mechanical field-by-field delta to catch dropped/re-ordered authors, wrong years, wrong venues, and bad DOIs/arXiv ids. The main agent (never a shard) assigns the MATCH/MINOR/MISMATCH verdict per reference, and exports a side-by-side spreadsheet. Use when user says "citation crosscheck", "double-blind citation check", "verify bib against scholar", "bib field audit", "引用交叉核对", or before submission when bibliography FIELD accuracy (not just existence) must be certified.DateFără avertismente★ 17,8 K↓ —
- Gong AutomationComposioHQ/awesome-claude-skillsAutomate Gong conversation intelligence -- retrieve call recordings, transcripts, detailed analytics, speaker stats, and workspace data -- using natural language through the Composio MCP integration.DateFără avertismente★ 77,6 K↓ —Apare și în 1 alt depozit
- Neon AutomationComposioHQ/awesome-claude-skillsAutomate Neon serverless Postgres operations -- manage projects, branches, databases, roles, and connection URIs via the Composio MCP integration.DateFără avertismente★ 77,6 K↓ —Apare și în 1 alt depozit
- analyzebrycewang-stanford/Auto-Empirical-Research-SkillsEnd-to-end data analysis dispatching Coder and Data-engineer for implementation, coder-critic for review. Supports R, Stata, Python, Julia. Replaces /data-analysis.DateFără avertismente★ 4,7 K↓ —
- astropyforyourhealth111-pixel/Vibe-SkillsComprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.DateFără avertismente★ 3,7 K↓ —
- academic-baselinebrycewang-stanford/Auto-Empirical-Research-SkillsUse when working on any empirical academic research context — paper writing, data analysis, literature review, or any task involving citations, results, or publication artifacts. Establishes non-negotiable principles that govern all other superpapers skills.DateFără avertismente★ 4,7 K↓ —
- polarsforyourhealth111-pixel/Vibe-SkillsFast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.DateFără avertismente★ 3,7 K↓ —
- dataset-quality-auditzebbern/claude-code-guideRun comprehensive quality checks on tabular data (CSV/Excel/TSV/JSON), detecting missing values, duplicates, outliers, format issues, and type inconsistencies to produce an overall score, grade, and actionable suggestions. Triggered when users ask to check data quality, find missing or duplicate values, detect outliers, validate formats, profile data, or clean data.DateFără avertismente★ 4,7 K↓ —
- database-scoutzebbern/claude-code-guideExplore SQLite and PostgreSQL databases: list tables, inspect schemas (columns/types/constraints), preview data, generate Mermaid ER diagrams, and run safe read-only queries. Triggered by requests to explore a database, view table structures, describe tables, generate diagrams, or query data, and by keywords like database exploration, schema, ER diagram, or SQL query.DateFără avertismente★ 4,7 K↓ —
- sql-insightzebbern/claude-code-guideTranslate natural language to SQL, optimize query performance, and interpret EXPLAIN plans for SQLite and PostgreSQL. Triggered when users ask to convert questions into SQL, improve slow queries, tune indexes, analyze execution plans, or mention keywords like NL2SQL, query tuning, or full table scan.DateFără avertismente★ 4,7 K↓ —
- setupbrycewang-stanford/Auto-Empirical-Research-SkillsDiverga v12.0 setup wizard. 4-step researcher profile setup. Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference. Triggers: setup, configure, 설정, installDateFără avertismente★ 4,7 K↓ —
- i3brycewang-stanford/Auto-Empirical-Research-SkillsRAG Builder with Parallel Document Processing Vector database construction with local embeddings (zero cost) Handles PDF download, text extraction, chunking, and vector database creation Absorbed B5 (Parallel Document Processor) capabilities Use when: building RAG, creating vector database, downloading PDFs, embedding documents, batch processing Triggers: build RAG, create vector database, download PDFs, embed documents, batch PDF processingDateFără avertismente★ 4,7 K↓ —
- i1brycewang-stanford/Auto-Empirical-Research-SkillsPaper Retrieval Agent - Multi-database paper fetching from Semantic Scholar, OpenAlex, arXiv Handles rate limiting, deduplication, and PDF URL extraction Use when: fetching papers, searching databases, paper retrieval Triggers: fetch papers, retrieve papers, database search, Semantic Scholar, OpenAlex, arXivDateFără avertismente★ 4,7 K↓ —