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.
46.100 de skill-uri din 2.198 de depozite · actualizat acum 17 ore
45.010 skill-uri
- 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★ 55,2 K↓ —Apare și în 1 alt depozit
- 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★ 55,2 K↓ —Apare și în 1 alt depozit
- app-agbKlotzkette/claude-fuer-deutsches-rechtFür App AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- onekgpdK-Dense-AI/scientific-agent-skillsQueries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which individuals are homozygous-reference at a position, which variants exist in the dataset or carried by specified individuals in a gene or region, the relatedness between two specified individuals. Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations.ȘtiințăFără avertismente★ 55,2 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★ 55,2 K↓ —Apare și în 1 alt depozit
- employment-compliancecbrock84/headcountCovers the employment rules that carry real penalties — exempt and non-exempt classification, overtime and hours, employee versus contractor status, work authorization and recordkeeping, accommodation requests, and the notices and retention obligations that go with them. Use this to classify a role, review a contractor arrangement, respond to an accommodation request, work out what records to keep and for how long, or sanity-check a practice you inherited.JuridicFără avertismente★ 2,5 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★ 55,2 K↓ —Apare și în 1 alt depozit
- nda-typen-vergleichKlotzkette/claude-fuer-deutsches-rechtFür NDA-Typen Vergleich: entwickelt Ziel, Vergleich und Eskalation; Ergebnis: Verhandlungs- oder Eskalationslinie.JuridicFără avertismente★ 1,8 K↓ —
- 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★ 55,2 K↓ —Apare și în 1 alt depozit
- transaktionen-ddKlotzkette/claude-fuer-deutsches-rechtFür Energie-Transaktionen und Due Diligence: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- 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★ 55,2 K↓ —
- portfolio-governancecbrock84/headcountGoverns the portfolio of work — intake, prioritization, stage gates, resource contention, and stopping things. Use this to set up intake and prioritization, run a stage gate, decide between competing initiatives, resolve resource contention across projects, or work out why everything is in flight and nothing is finishing.AlteleFără avertismente★ 2,5 K↓ —
- latchbio-integrationK-Dense-AI/scientific-agent-skillsBuilds, registers, debugs, and operates bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and monitoring runs.DevOpsFără avertismente★ 55,2 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★ 55,2 K↓ —Apare și în 1 alt depozit
- 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★ 55,2 K↓ —
- instagramsickn33/agentic-awesome-skillsIntegracao completa com Instagram via Graph API. Publicacao, analytics, comentarios, DMs, hashtags, agendamento, templates e gestao de contas Business/Creator.DateFără avertismente★ 48,7 K↓ —
- 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★ 55,2 K↓ —
- agent-platform-deploygoogle/skillsDeploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` skill).OficialDevOpsFără avertismente★ 21,7 K↓ —
- markdown-to-word-mermaidgithub/awesome-copilotExport Markdown containing Mermaid code fences to Word (.docx) with embedded SVG diagrams and PNG fallbacks. Use when diagram sharpness, Office-compatible labels, or page-aware placement matters. Not for Word-to-Markdown conversion, editable Office shapes, or general slide creation.DocumenteFără avertismente★ 40,6 K↓ —
- portfolio-strategycbrock84/headcountDecides where capital and attention go across business lines, products, and markets — what to fund, hold, harvest, or exit, and on what evidence. Use this to allocate budget across businesses, evaluate whether a product line should continue, decide whether to exit one, structure a portfolio review, or when several initiatives compete for the same limited investment.FinanțeFără avertismente★ 2,5 K↓ —
- sozialdaten-sgbKlotzkette/claude-fuer-deutsches-rechtFür Sozialdaten im Datenschutzvorfall — SGB I und SGB X: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- gruen-fehlerkatalogKlotzkette/claude-fuer-deutsches-rechtFür Grün Fehlerkatalog: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- scientific-schematicsK-Dense-AI/scientific-agent-skillsGenerates scientific diagram drafts using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.7 Flash for quality review. Refines when the review requests improvement, with at most two generations. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.ȘtiințăFără avertismente★ 55,2 K↓ —
- 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★ 55,2 K↓ —Apare și în 1 alt depozit
qiskit
K-Dense-AI/scientific-agent-skills
De la autor
Builds, simulates, transpiles, and executes quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill qiskit -a claude-code
Se instalează în .claude/skills/qiskit/ · 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
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Fișiere (15)
- SKILL.md
- references/algorithms.md
- references/backends.md
- references/circuits.md
- references/migration.md
- references/patterns.md
- references/primitives.md
- references/setup.md
- references/sources.md
- references/testing.md
- references/transpilation.md
- references/visualization.md
- încă 3