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 41 de minute
715 skill-uri
- migrateparcadei/Continuous-Claude-v3Migration workflow - research → analyze → plan → implement → reviewȘtiințăFără avertismente★ 3,9 K↓ —
- research-agentparcadei/Continuous-Claude-v3Research agent for external documentation, best practices, and library APIs via MCP toolsȘtiințăFără avertismente★ 3,9 K↓ —
- phylogeneticsK-Dense-AI/scientific-agent-skillsBuilds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein families, and cautiously interpreted dated phylogenies.ȘtiințăFără avertismente★ 53,4 K↓ —
- pyopenmsK-Dense-AI/scientific-agent-skillsProcesses mass spectrometry data with pyOpenMS. Supports proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.ȘtiințăFără avertismente★ 53,4 K↓ —
- repo-research-analystparcadei/Continuous-Claude-v3Analyze repository structure, patterns, conventions, and documentation for understanding a new codebaseȘtiințăFără avertismente★ 3,9 K↓ —
- researchparcadei/Continuous-Claude-v3Document codebase as-is with thoughts directory for historical contextȘtiințăFără avertismente★ 3,9 K↓ —
- icp-research-assistantirinabuht12-oss/marketing-skillsClaude skills for marketing: 49 free marketing skills for Claude Code and claude.ai (Google Ads, Meta Ads, SEO, AI visibility) + the Ryze Google Ads MCP / Meta Ads MCP: claude mcp add ryze --transport http https://connector.get-ryze.ai/mcpȘtiințăFără avertismente★ 5,2 K↓ —
- amazon-listing-competitor-analysis-skillbrowser-act/skillsThis skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.ȘtiințăFără avertismente★ 6,2 K↓ —
- StatsPAI_skillbrycewang-stanford/Auto-Empirical-Research-SkillsUse when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting muȘtiințăFără avertismente★ 4,7 K↓ —
- web-research-assistantbrowser-act/skillsAI-powered web research assistant that leverages BrowserAct API to supplement restricted web access by searching the internet for additional information. Designed for OpenClaw and Claude Code.ȘtiințăFără avertismente★ 6,2 K↓ —
- ecommerce-seller-infobrowser-act/skillsExtract seller or merchant profile data from marketplace platform seller pages. Returns seller name, rating, review count, positive feedback percentage, joined date, and return policy. Works on Amazon seller pages, eBay seller pages, and any e-commerce site with seller profiles. Use when: seller information, merchant profile, seller rating, marketplace seller data, seller details, vendor profile, store information, seller feedback, merchant rating, seller review count, get seller info, ebay seller page, amazon seller profile, marketplace vendor analysis, seller research.ȘtiințăFără avertismente★ 6,2 K↓ —
- research-externalparcadei/Continuous-Claude-v3External research workflow for docs, web, APIs - NOT codebase explorationȘtiințăFără avertismente★ 3,9 K↓ —
- perplexity-searchparcadei/Continuous-Claude-v3AI-powered web search, research, and reasoning via PerplexityȘtiințăFără avertismente★ 3,9 K↓ —
- perplexitysoftaworks/agent-toolkitWeb search and research using Perplexity AI. Use when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7) or workspace questions.ȘtiințăFără avertismente★ 2,6 K↓ —
- orchestraterohitg00/pro-workflowWire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.ȘtiințăFără avertismente★ 2,9 K↓ —
- gepettosoftaworks/agent-toolkitCreates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.ȘtiințăFără avertismente★ 2,6 K↓ —
- researchWeizhena/Deep-Research-skills对目标话题进行初步调研，生成调研outline。用于学术调研、benchmark调研、技术选型等场景。ȘtiințăFără avertismente★ 2,4 K↓ —
- researchWeizhena/Deep-Research-skillsConduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.ȘtiințăFără avertismente★ 2,4 K↓ —Apare și în 1 alt depozit
- researchWeizhena/Deep-Research-skillsConduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.ȘtiințăFără avertismente★ 2,4 K↓ —
- stata-table-builderbrycewang-stanford/Auto-Empirical-Research-SkillsBuild and review paper-ready regression, balance, and summary tables from Stata outputs. Use when the user needs a clean table for a draft, appendix, or coauthor share-out.ȘtiințăFără avertismente★ 4,7 K↓ —
- kaggle-researchbrycewang-stanford/Auto-Empirical-Research-SkillsUse when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.ȘtiințăFără avertismente★ 4,7 K↓ —
- fred-economic-dataforyourhealth111-pixel/Vibe-SkillsQuery FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring U.S. and international economic indicators.ȘtiințăFără avertismente★ 3,7 K↓ —
- paper-submissionbrycewang-stanford/Auto-Empirical-Research-SkillsEvaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".ȘtiințăFără avertismente★ 4,7 K↓ —
- 48-de-AIGC-skillsbrycewang-stanford/Auto-Empirical-Research-Skills🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.ȘtiințăFără avertismente★ 4,7 K↓ —