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.
9.461 de skill-uri din 277 de depozite · actualizat acum 40 de minute
722 de skill-uri
- paper-figurebrycewang-stanford/Auto-Empirical-Research-SkillsGenerate publication-quality figures and tables from experiment results. Use when user says "画图", "作图", "generate figures", "paper figures", or needs plots for a paper.ȘtiințăFără avertismente★ 4,7 K↓ —
- paper-searchopen-gitagent/opengapAcademic paper search via Google Scholar using Serper APIȘtiințăFără avertismente★ 3 K↓ —
- researchopen-gitagent/opengapResearches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'ȘtiințăFără avertismente★ 3 K↓ —
- research-implement-featurewanshuiyin/Auto-claude-code-research-in-sleepBuild a working artifact from a plain "implement X for me" request: a running end-to-end spine first, then one feature per rung, with every under-determined decision written to an assumption ledger BEFORE the code that depends on it and a cross-model sweep for the ones that slipped through undeclared. Use when user says "给我实现", "implement X", "帮我做一个能跑的", "先搭个原型再加功能", "build this feature", "prototype then extend", or hands over a capability description rather than an experiment plan.ȘtiințăVerifică întâi★ 17,8 K↓ —
- claudebergside/awesome-design-skillsA research-journal aesthetic printed on warm stone — authoritative, editorial, almost achromatic. Pages live on warm ivory parchment (never pure white), with near-black slate as the dominant ink.ȘtiințăFără avertismente★ 3,3 K↓ —
- paper-writingwanshuiyin/Auto-claude-code-research-in-sleepWorkflow 3: Full paper writing pipeline that goes from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.ȘtiințăVerifică întâi★ 17,8 K↓ —
- paper-writingwanshuiyin/Auto-claude-code-research-in-sleepWorkflow 3: Full paper writing pipeline that goes from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.ȘtiințăVerifică întâi★ 17,8 K↓ —
- paper-writewanshuiyin/Auto-claude-code-research-in-sleepDraft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.ȘtiințăVerifică întâi★ 17,8 K↓ —
- literature-searchbrycewang-stanford/Auto-Empirical-Research-SkillsUse when the user asks to search for papers, review literature, find references on a topic, verify a paper exists, or build a bibliography. Enforces web verification of every citation via web fetch to prevent hallucinated references.ȘtiințăFără avertismente★ 4,7 K↓ —
- paper-referee-revisebrycewang-stanford/Auto-Empirical-Research-SkillsRevise an academic paper based on journal referee reports. Reads referee comments from review report or annotated manuscript, then directly modifies main.tex one comment at a time with user approval. Generates response letter after revision. Trigger when user says "referee revise" / "paper-referee-revise" / "审稿意见修改" / "根据审稿人意见修改" / "referee report".ȘtiințăFără avertismente★ 4,7 K↓ —
- causal-mlbrycewang-stanford/Auto-Empirical-Research-SkillsThis skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.ȘtiințăFără avertismente★ 4,7 K↓ —
- citebrycewang-stanford/Auto-Empirical-Research-SkillsFinds a paper by title, author, or DOI, adds BibTeX to references.bib, and shows citation syntax. Use when adding a reference.ȘtiințăFără avertismente★ 4,7 K↓ —
- initbrycewang-stanford/Auto-Empirical-Research-SkillsFills all [FILL:] placeholders across the template to initialize a new research project. Use when setting up a freshly cloned project.ȘtiințăFără avertismente★ 4,7 K↓ —
- clinical-decision-supportforyourhealth111-pixel/Vibe-SkillsGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.ȘtiințăFără avertismente★ 3,7 K↓ —
- content-research-writeranbeime/skill内容创作者、技术写作员在撰写博客、深度文章或技术文档时，使用此技能可开启全流程写作协作。它能帮你研究资料、构建大纲、逐段打磨并自动添加引用，快速优化Hook，让你高效产出高质量内容，告别孤军奋战！ȘtiințăFără avertismente★ 8,5 K↓ —
- data-scientistcode-yeongyu/oh-my-openagentProcesses and analyzes data with resident-kernel engines (DuckDB, Polars) and one-shot tools. Use for CSV/parquet/JSON analysis, group-by/join/aggregation, time series, distributions, cleaning, or plotting a dataset.ȘtiințăFără avertismente★ 70,2 K↓ —
- ulw-researchcode-yeongyu/oh-my-openagentRuns maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.ȘtiințăFără avertismente★ 70,2 K↓ —
- nv-generate-vae-finetuneNVIDIA/skillsUsed for finetuning the NV-Generate-CTMR MAISI VAE from CT/MRI NIfTI datalists. Not for clinical or production data approval.ȘtiințăFără avertismente★ 3,7 K↓ —
- paper-explainerZJU-REAL/Easel科研论文解读：解析 arXiv/PDF 的公式与图表，提炼问题、贡献、方法、关键图和结论，再产出 B站/视频号解读视频或知乎/公众号图文。 当用户说“论文解读、讲论文、论文转视频/图文、科研科普、arXiv、学术视频”时使用。 本 SKILL 从论文做内容；video-to-article 从视频做图文，doc-convert 只转换文档格式。ȘtiințăFără avertismente★ 3,9 K↓ —
- rdkitforyourhealth111-pixel/Vibe-SkillsCore cheminformatics toolkit for SMILES/SDF/InChI parsing, descriptors (MW, LogP, TPSA), fingerprints, ECFP/Morgan fingerprints, substructure search, 2D/3D generation, similarity, reactions, and datamol-style molecule standardization when no separate wrapper skill is routed.ȘtiințăFără avertismente★ 3,7 K↓ —
- pymatgenforyourhealth111-pixel/Vibe-SkillsMaterials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.ȘtiințăFără avertismente★ 3,7 K↓ —
- nv-segment-ctmrNVIDIA/skillsUsed for running NV-Segment-CTMR on CT or MRI NIfTI volumes and recording label-map evidence. Not for clinical interpretation.ȘtiințăFără avertismente★ 3,7 K↓ —
- infographicsforyourhealth111-pixel/Vibe-SkillsCreate professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.ȘtiințăFără avertismente★ 3,7 K↓ —
- cs-foundationsforyourhealth111-pixel/Vibe-SkillsMaster discrete mathematics, logic, formal proofs, and computational thinking. Build the mathematical foundation for all computer science.ȘtiințăFără avertismente★ 3,7 K↓ —