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.
48.622 de skill-uri din 2.355 de depozite · actualizat acum 4 ore
48.622 de skill-uri
- output-versandKlotzkette/claude-fuer-deutsches-rechtFür Output und Versandsteuerung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- flowkitK-Dense-AI/scientific-agent-skillsAnalyzes flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces. Use for reproducible gate counts, population percentages, gated fluorescence summaries, or reproducing a FlowJo analysis in Python. For FCS metadata inspection or file-format repair alone, use FlowIO.InginerieFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- genimlK-Dense-AI/scientific-agent-skillsSupports audited local Geniml genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- autoskillK-Dense-AI/scientific-agent-skillsAnalyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- pytdcK-Dense-AI/scientific-agent-skillsProvides Therapeutics Data Commons workflows through PyTDC for registry discovery, dataset access, task-aware splits, evaluator metrics, benchmark groups, and bounded molecular-oracle scoring. Use when working with TDC therapeutic ML datasets or benchmarks.ProductivitateFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- maintenance-and-reliabilitycbrock84/headcountKeeps production assets available — ranking equipment by consequence of failure, setting preventive and predictive intervals, sizing spares, and moving a plant off reactive maintenance. Use this to build or fix a maintenance program, decide what to put on a PM schedule, diagnose repeat failures on one asset, justify spares inventory, or work out why a plant that maintains everything still has unplanned downtime.PlanificareFără avertismente★ 2,6 K↓ —
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestareFără avertismente★ 55,6 K↓ —
- transformersK-Dense-AI/scientific-agent-skillsHugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.MediaFără avertismente★ 55,6 K↓ —
- rowanK-Dense-AI/scientific-agent-skillsRowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.DevOpsFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- slidevLeoYeAI/agent-master-skillsCreate and present web-based slides for developers using Markdown, Vue components, code highlighting, animations, and interactive features. Use when building technical presentations, conference talks, or teaching materials.DocumenteFără avertismente★ 2,2 K↓ —
- networkxK-Dense-AI/scientific-agent-skillsCreates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- ontology-term-resolutionK-Dense-AI/scientific-agent-skillsResolves free-text scientific labels to ontology term IDs and validates existing CURIEs against the EBI Ontology Lookup Service (OLS4). Also looks up prefixes in Bioregistry, resolves compact identifiers via Identifiers.org, maps lab shorthand with ZOOMA, and builds Ontobee term pages. Use whenever an ontology identifier must be produced or checked - annotating tissue, cell type, disease, phenotype, assay, chemical, organism, sex, or developmental stage fields; preparing metadata for GEO, ENA, BioSamples, CELLxGENE, HCA, or ISA-Tab submission; auditing a metadata table of term IDs; checking whether a term is obsolete and what replaced it; or deciding HPO vs HP. Triggers include "ontology term", "ontology ID", "CURIE", "controlled vocabulary", "UBERON", "CL:", "MONDO", "HPO", "EFO", "ChEBI", "NCBITaxon", "GO term", "PATO", "Zooma", "Bioregistry", "Identifiers.org", "Ontobee", "annotate this tissue/cell type/disease", and any request to emit or verify an identifier shaped like PREFIX:0001234.ȘtiințăFără avertismente★ 55,6 K↓ —
- test-driven-developmentcbrock84/headcountDrives implementation by writing a failing test first, then the smallest code that passes it. Use this before writing implementation code for any feature or bugfix, when a bug needs a regression test, when existing code is hard to change safely, or when someone asks whether a change is covered. Also use to decide what is worth testing and what is not.TestareFără avertismente★ 2,6 K↓ —
- founder-competitorsJakeschincariol/founder-skillMaps every competitor and the gap they leave. Finds the direct competitors, indirect ones and the substitutes a buyer would use instead, from public sources only, and records what each sells, at what price, how they position themselves and what their customers complain about in public reviews, every fact with a link. Ends with a positioning map and the gap the new business can own. Use when the user says "who are my competitors", "is this market crowded", "what else is out there", "competitor analysis", "find the gap", or "who am I up against".AlteleFără avertismente★ 2,3 K↓ —
- neuropixels-analysisK-Dense-AI/scientific-agent-skillsAnalyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.InginerieFără avertismente★ 55,6 K↓ —
- production-managementcbrock84/headcountRuns the production schedule — sequencing and releasing work, managing work in process and changeovers, and holding the promised date when the floor and the order book disagree. Use this to build or fix a production schedule, decide what to run next, diagnose why lead times are growing while machines look busy, set up OEE or throughput measurement, or choose between make-to-stock and make-to-order for a product line.FinanțeFără avertismente★ 2,6 K↓ —
- business-continuity-and-resiliencecbrock84/headcountPlans for operating through disruption — impact analysis, recovery objectives, continuity plans, and the exercises that prove they work. Use this to run a business impact analysis, set RTO and RPO, write or test a continuity plan, prepare for a supplier or site failure, or answer a customer's resilience questionnaire.TestareFără avertismente★ 2,6 K↓ —
- ktxKaelio/ktxInstalls and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.DateFără avertismente★ 1,6 K↓ —
- nature-paper2pptYuan1z0825/nature-skillsCreate or improve a Chinese academic PPTX from a scientific paper or research reading notes, with source figures and speaker notes. Use for 论文做PPT、文献汇报、组会PPT and paper-based conference or defense presentations.DocumenteFără avertismente★ 51,7 K↓ —
- restore-credentialsandroid/skillsProvides knowledge and workflows to implement Android's Restore Credentials feature using the androidx.credentials library. Use this skill to create, sign in with, and delete restore keys, enabling silent user sign-in on new devices after a restore. It covers version compatibility, dependencies, server-side prerequisites, and the complete client-side implementation for creating, retrieving, and clearing restore keys.OficialAlteleFără avertismente★ 10,2 K↓ —
- pathway-enrichmentK-Dense-AI/scientific-agent-skillsPerforms pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".TestareFără avertismente★ 55,6 K↓ —
- labor-and-union-relationscbrock84/headcountManages the relationship with a represented workforce — administering a collective agreement, handling grievances, understanding what supervisors may and may not say, and preparing for bargaining. Use this for a grievance or arbitration question, a work rule change in a represented unit, supervisor guidance during organizing, contract interpretation and past practice, or preparation for negotiations.JuridicFără avertismente★ 2,6 K↓ —
- customer-success-managementcbrock84/headcountRuns the ongoing relationship with accounts after the sale — segmenting coverage against account value, building a health score that predicts rather than describes, running reviews customers find worth attending, forecasting renewals honestly, and finding expansion that follows usage instead of quota. Use this to design a customer success motion, decide who gets a named contact, work out why renewals surprise you, or fix a health score everyone ignores.DesignFără avertismente★ 2,6 K↓ —
- gke-ai-troubleshooting-tpu-vbar-oomgoogle/skillsDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.OficialProductivitateFără avertismente★ 21,8 K↓ —
research-with-sources
inkeep/open-knowledge
ȘtiințăActualizat acum 22 de ore
De la autor
Investigate a topic against preserved sources and write a draft-status research article under `research/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when asked to research a topic, compare options, synthesize sources, gather evidence, or extend an existing research doc. Carries the full procedure: scan existing coverage, agree a research rubric, capture every source verbatim before analyzing, write the article incrementally so a crash never loses work, cite every claim, and link it back into the graph. Does not promote findings to canonical knowledge — that is the sibling `consolidate-notes` skill, after a decision lands.
Instalare
npx skills add inkeep/open-knowledge --skill research-with-sources -a claude-code
Se instalează în .claude/skills/research-with-sources/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (GPL-3.0) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: GPL-3.0
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 89
Securitate100
Proveniență84
Întreținere100
Licență80
Adopție58
Fișiere (1)
- SKILL.md