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.
7.004 skill-uri din 180 de depozite · actualizat acum 19 minute
193 de skill-uri
- 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↓ —
- deepstream-devNVIDIA/skillsNVIDIA DeepStream SDK development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker integration.DateFără avertismente★ 3,7 K↓ —
- g1brycewang-stanford/Auto-Empirical-Research-SkillsVS-Enhanced Journal Matcher with Journal Intelligence MCP — Real-time journal data pipeline with checkpoint-based human decisions. Uses OpenAlex + Crossref APIs for live metrics. Light VS applied: Avoids IF-centric recommendations + multi-dimensional matching strategy Use when: selecting target journals, planning submissions, comparing publication options Triggers: journal, submission, impact factor, academic journal, publication, submitDateFără 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- pubmed-databaseforyourhealth111-pixel/Vibe-SkillsDirect REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.DateFără avertismente★ 3,7 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↓ —
- geo-databaseforyourhealth111-pixel/Vibe-SkillsAccess NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.DateFără avertismente★ 3,7 K↓ —
- infographicZJU-REAL/Easel将数据或文字内容转化为可视化信息图，支持静态（AntV）和动画 GIF 两种模式。当用户需要制作信息图、数据可视化、流程图、对比图、动画图表、GIF 图表、思维导图、SWOT 分析图时调用。本地渲染信息图/GIF 动画；要单张静态图片 URL 用 chart-visualization，要 CSV/JSON→整页报告用 data-reportDateFără avertismente★ 3,9 K↓ —
- uniprot-databaseforyourhealth111-pixel/Vibe-SkillsDirect REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For broader biological evidence lookup across databases, use bio-database-evidence. Use this for direct HTTP/REST work or UniProt-specific control.DateFără avertismente★ 3,7 K↓ —
- data-reportZJU-REAL/Easel把 CSV、Excel 或 JSON 数据生成包含 KPI、图表和洞察的完整可视化报告页。当用户说“数据报告、CSV/Excel 转报告、做 KPI 看板、生成可视化报告页”时使用。单张图表用 chart-visualization；信息图或 GIF 动画图表用 infographic。DateFără avertismente★ 3,9 K↓ —
- skill-publish-analyticsZJU-REAL/Easel分析发布日志数据，从发布时间、标签效果、内容类型、粉丝增长四个维度归因内容表现，输出可执行的优化建议。 当用户说"发布数据分析""归因分析""什么时间发好""标签效果""内容表现分析""发布日志分析"时使用。 和 skill-social-performance-review 的区别：本 SKILL 从发布日志做四维归因，review 做跨平台月度组合复盘。DateFără avertismente★ 3,9 K↓ —
- xanforyourhealth111-pixel/Vibe-SkillsHigh-performance CSV processing with xan CLI for large tabular datasets, streaming transformations, and low-memory pipelines.DateFără avertismente★ 3,7 K↓ —
- kermt-inferNVIDIA/skillsRun predictions with a finetuned KERMT checkpoint on a SMILES-only CSV. The skill validates that the input ckpt has task FFN heads (refuses pretrain ckpts with a redirect to kermt-finetune), validates the CSV, prepares the data (clean + rdkit_2d features), then launches main.py predict inside the kermt container (blocking, minutes-scale).DateFără avertismente★ 3,7 K↓ —
- kermt-finetuneNVIDIA/skillsFinetune a pretrained KERMT encoder on a labeled CSV. Validate the checkpoint and data, prepare features, and run containerized training. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Write model bundles, prepared data, logs, and trained models to user-selected host directories.DateFără avertismente★ 3,7 K↓ —
- markitdownforyourhealth111-pixel/Vibe-SkillsConvert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.DateFără avertismente★ 3,7 K↓ —
- spreadsheetforyourhealth111-pixel/Vibe-SkillsUse when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.DateFără avertismente★ 3,7 K↓ —
- exploratory-data-analysisforyourhealth111-pixel/Vibe-SkillsPerform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.DateFără avertismente★ 3,7 K↓ —
- statistics-mathforyourhealth111-pixel/Vibe-SkillsStatistics, probability, linear algebra, and mathematical foundations for data scienceDateFără avertismente★ 3,7 K↓ —
- timesfm-forecastingK-Dense-AI/scientific-agent-skillsPerforms zero-shot time-series forecasting with Google's TimesFM, including regular-grid CSV preparation, quantile forecasts, XReg covariates, and held-out evaluation. Uses the Apache-licensed TimesFM 2.5 checkpoint by default and documents the distinct TimesFM 3.0 multivariate API and weight-license requirements.DateFără avertismente★ 53,4 K↓ —
- bioservicesK-Dense-AI/scientific-agent-skillsProvides a Python interface to bioinformatics services including UniProt, KEGG, ChEMBL, Reactome, QuickGO, and UniChem. Used for cross-database protein annotation, pathway retrieval, chemical identifier mapping, and integrated biological data workflows with BioServices.DateFără avertismente★ 53,4 K↓ —