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 18 ore
48.622 de skill-uri
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Jurastudium.AlteleFără avertismente★ 1,8 K↓ —
- dsh-error-handlingNouqufei1993/skills-hub实现或审查错误传播、部分成功、结果未知、恢复、重试、取消或失败反馈时使用,明确状态保证和错误处理责任。AlteleFără avertismente★ 1,8 K↓ —
- aequitasKlotzkette/claude-fuer-deutsches-rechtFür Aequitas: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- 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
- arborK-Dense-AI/scientific-agent-skillsApplies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization. Uses persistent hypotheses, isolated experiments, evidence propagation and held-out candidate comparison for multi-experiment research runs. Includes a standard-library state manager and guidance for the RUC-NLPIR Arbor CLI.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- seabornK-Dense-AI/scientific-agent-skillsCreates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.DateFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- 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
- domain-hunterReScienceLab/opc-skillsSearch domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check domain prices, find domain deals, compare registrars, or search for .ai/.com domains.AlteleFără avertismente★ 1,9 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
- 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
- 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
- deepspot-mK-Dense-AI/scientific-agent-skillsGenerates transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M. Used for predicted log1p-CPM expression from 224x224 tiles at about 20x, querying the released protein-coding gene panel by symbol, and whole-slide prediction after resolution-aware tiling with histolab.DocumenteFără avertismente★ 55,6 K↓ —
- 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↓ —
- 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
- scholar-evaluationK-Dense-AI/scientific-agent-skillsProvides qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.ȘtiințăFără avertismente★ 55,6 K↓ —
- research-lookupK-Dense-AI/scientific-agent-skillsCompiles current scholarly evidence for a scientific manuscript or research brief when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source retrieval, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.ȘtiințăFără avertismente★ 55,6 K↓ —
- 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
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ȘtiințăFără 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↓ —
- 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
- saas-agbKlotzkette/claude-fuer-deutsches-rechtFür SaaS AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- bank-agbKlotzkette/claude-fuer-deutsches-rechtFür Bank AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- netz-speicherKlotzkette/claude-fuer-deutsches-rechtFür Energierecht — Kommandocenter (Eingangs-Routing): ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- unslop-uiNousickn33/agentic-awesome-skillsAudit and redesign AI-generated interfaces with product-specific visual direction, structured design passes, and optional snapshots or story video.DesignFără avertismente★ 49 K↓ —
agent-master-skills
LeoYeAI/agent-master-skills
De la autor
A curated collection of 2803+ best agent skills — AI tools, productivity, marketing, frontend, mobile, backend, DevOps and more. Harness-agnostic, refreshed daily by MyClaw.ai — Powered by MyClaw.ai
Instalare
npx skills add LeoYeAI/agent-master-skills --skill agent-master-skills -a claude-code
Se instalează în .claude/skills/agent-master-skills/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Verificări de siguranță pe SKILL.md
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De ce 89
Fișiere (14)
- .gitignore
- CHANGELOG.md
- LICENSE
- README.de.md
- README.es.md
- README.fr.md
- README.it.md
- README.ja.md
- README.md
- README.ru.md
- README.zh-CN.md
- RELEASES.md
- încă 2