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.
14.533 de skill-uri din 417 depozite · actualizat acum 4 ore
966 de skill-uri
- 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↓ —
- dicom-metadata-extractNVIDIA/skillsUsed for extracting selected metadata from one DICOM file and flagging standard-tag PHI presence. Not for anonymization or clinical use.ȘtiințăFără avertismente★ 3,7 K↓ —
- dicom-series-preflightNVIDIA/skillsUsed for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.ȘtiințăFără avertismente★ 3,7 K↓ —
- dicom-series-to-volumeNVIDIA/skillsUsed for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.ȘtiințăFără avertismente★ 3,7 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↓ —
- x-researchdavepoon/buildwithclaudeSearch and inspect current public X posts, trends, profiles, profile posts, media, and replies through AgentBody. Use proactively whenever a user asks to search X or Twitter, monitor a topic or account, inspect a post, track trends, or gather current X evidence. Prefer this Skill over browser search and built-in web search.ȘtiințăFără avertismente★ 3,7 K↓ —
- migrateparcadei/Continuous-Claude-v3Migration workflow - research → analyze → plan → implement → reviewȘtiințăFără avertismente★ 3,9 K↓ —
- paper-compilebrycewang-stanford/Auto-Empirical-Research-SkillsCompile LaTeX paper to PDF, fix errors, and verify output. Use when user says "编译论文", "compile paper", "build PDF", "生成PDF", or wants to compile LaTeX into a submission-ready PDF.ȘtiințăFără avertismente★ 4,7 K↓ —
- research-agentparcadei/Continuous-Claude-v3Research agent for external documentation, best practices, and library APIs via MCP toolsȘtiințăFără avertismente★ 3,9 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↓ —
- 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↓ —
- pymooK-Dense-AI/scientific-agent-skillsSolves and validates single-, multi-, and many-objective optimization with pymoo, including NSGA-II, NSGA-III, MOEA/D, constraints, Pareto approximations, reference directions, and ZDT/DTLZ benchmarks for engineering and research problems.ȘtiințăFără avertismente★ 53,8 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↓ —
- 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↓ —
- medchemK-Dense-AI/scientific-agent-skillsApplies medicinal chemistry filters for compound triage, using drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.ȘtiințăFără avertismente★ 53,8 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★ 53,8 K↓ —
- paper-posterbrycewang-stanford/Auto-Empirical-Research-SkillsGenerate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says "做海报", "制作海报", "conference poster", "make poster", "生成poster", "poster session", or wants to create a poster for a conference presentation.ȘtiințăFără avertismente★ 4,7 K↓ —
- mcp-chainingparcadei/Continuous-Claude-v3Research-to-implement pipeline chaining 5 MCP tools with graceful degradationȘtiințăFără avertismente★ 3,9 K↓ —
- researchparcadei/Continuous-Claude-v3Document codebase as-is with thoughts directory for historical contextȘtiințăFără 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★ 53,8 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↓ —
- glycoengineeringK-Dense-AI/scientific-agent-skillsAnalyzes and engineers protein glycosylation by scanning canonical N-glycosylation sequons, describing S/T-rich regions, checking curated glycan evidence, and preparing NetNGlyc, NetOGlyc and GlycoSHIELD workflows. Use for glycoprotein engineering, antibody Fc glycosylation, glycan shielding, and site-specific glycoproteomics interpretation.ȘtiințăFără avertismente★ 53,8 K↓ —
- perplexity-searchparcadei/Continuous-Claude-v3AI-powered web search, research, and reasoning via PerplexityȘtiințăFără avertismente★ 3,9 K↓ —