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
47.548 de skill-uri
- anschlussKlotzkette/claude-fuer-deutsches-rechtFür Gesellschaftsrecht — Allgemein: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- kaltstart-interviewKlotzkette/claude-fuer-deutsches-rechtFür /arbeitsrecht:kaltstart-interview: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.PlanificareFără avertismente★ 1,8 K↓ —
- change-requestKlotzkette/claude-fuer-deutsches-rechtFür Change Reqüst: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- 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
- understand-knowledgeEgonex-AI/Understand-AnythingAnalyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.AlteleFără avertismente★ 89,5 K↓ —
- pathmlK-Dense-AI/scientific-agent-skillsSupports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference. Use for whole-slide H&E, CODEX, Vectra, Mesmer, HoVer-Net, and HACTNet workflows.DocumenteFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- 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
- 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↓ —
- 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
- 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
- pydeseq2K-Dense-AI/scientific-agent-skillsPerforms bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.TestareFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- assessment-designcbrock84/headcountBuilds questions and assessments that measure what they claim — matching item type to the thing being assessed, writing distractors that diagnose, and telling a question that measures learning from one that measures reading speed or test-taking. Use this to write or review assessment items, design a unit check or diagnostic, work out why scores do not match classroom performance, or decide how much evidence a claim about mastery actually needs.DesignFără avertismente★ 2,6 K↓ —
- strategic-alliancescbrock84/headcountStructures partnerships that change what the business can do — technology integrations, channel and reseller arrangements, joint ventures, and OEM relationships. Use this to evaluate or structure a strategic partnership, decide between partnering and building, negotiate commercial terms of an alliance, or diagnose a partnership that is signed but not producing. For audience-borrowing partnerships, use `marketing:partnership-marketing`.MarketingFără avertismente★ 2,6 K↓ —
- daskK-Dense-AI/scientific-agent-skillsScales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.DateFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- pedagogy-reviewpedrohcgs/claude-code-my-workflowHolistic pedagogical review of a lecture deck (`.qmd` or `.tex`). Checks narrative arc, prerequisite assumptions, worked examples, notation clarity, and deck-level pacing. Use when user says "pedagogy review", "does this teach well?", "is the flow right?", "will students follow?", "review the narrative", or before teaching a deck for the first time. Read-only; produces a report.InginerieFără avertismente★ 1,7 K↓ —
- ehs-and-workplace-safetycbrock84/headcountRuns environment, health and safety on an operating site — hazard controls in order of effectiveness, incident recording and reporting obligations, and safety measurement that does not reward silence. Use this to build or audit a safety program, decide what controls a hazard actually needs, work out whether an injury is recordable or reportable, investigate an incident, or fix safety metrics that have stopped producing reports.FinanțeFără avertismente★ 2,6 K↓ —
- molfeatK-Dense-AI/scientific-agent-skillsFeaturizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained embeddings, configuration persistence, and molecule-to-label alignment.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- cobrapyK-Dense-AI/scientific-agent-skillsPerforms constraint-based metabolic modeling with COBRApy, including FBA, pFBA, FVA, gene knockouts, flux sampling, growth media, production envelopes, gap filling, and SBML model validation for systems biology and metabolic engineering.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- dokumente-intakeKlotzkette/claude-fuer-deutsches-rechtFür Dokumentenintake: ordnet Akte, Belege und Lücken; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Meinungsprüfer.AlteleFără avertismente★ 1,8 K↓ —
- liteparseK-Dense-AI/scientific-agent-skillsLocal document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.DocumenteFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- diffdockK-Dense-AI/scientific-agent-skillsPredicts protein-small-molecule binding poses with DiffDock and DiffDock-L from PDB or sequence plus SMILES/SDF/MOL2. Covers batch docking, pose triage, confidence interpretation, and validation. Use for molecular docking and virtual-screening pose generation, not binding-affinity prediction.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- pydicomK-Dense-AI/scientific-agent-skillsReads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.RedactareFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- pysamK-Dense-AI/scientific-agent-skillsProvides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- diagram-designcathrynlavery/diagram-designCreate branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel, treemap and marimekko, heatmap, bar and dumbbell, waterfall, line (slopegraph, ridgeline, streamgraph, bump), Gantt and scatter charts (bubble, beeswarm, box plot), high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, service blueprint, deployment, dependency graph, UML class, story map, or database schema diagrams as HTML/SVG/PNG, with .drawio, Mermaid, and .excalidraw import, plus lifecycle phase maps, block decomposition trees, and onboarding guidance.DesignFără avertismente★ 63,7 K↓ —
nature-paper-card
Yuan1z0825/nature-skills
ȘtiințăActualizat acum 18 ore
De la autor
Build a structured deep-reading Paper Card for one scientific paper, analysing methods, experiment-to-claim evidence, limitations, and research ideas. Use for 论文精读卡、方法拆解、证据链分析; not full-paper bilingual translation or formal peer review.
Instalare
npx skills add Yuan1z0825/nature-skills --skill nature-paper-card -a claude-code
Se instalează în .claude/skills/nature-paper-card/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Rulează scripturile incluseNu am văzut acces la rețeaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Securitate85
Proveniență95
Întreținere100
Licență100
Adopție73
Fișiere (22)
- README.md
- README_EN.md
- SKILL.md
- agents/openai.yaml
- evals/evals.json
- manifest.yaml
- references/card-schema.md
- references/evidence-and-provenance.md
- references/research-idea-gates.md
- scripts/audit_paper_card.py
- scripts/prepare_paper.py
- static/core/output-contract.md
- încă 10