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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 21 de ore
48.168 de skill-uri
- 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★ 2,5 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★ 55,5 K↓ —Apare și în 1 alt depozit
- ai-ml-governancecbrock84/headcountGoverns models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.DevOpsFără avertismente★ 2,5 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★ 55,5 K↓ —Apare și în 1 alt depozit
- generate-imageK-Dense-AI/scientific-agent-skillsGenerates or edits images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams, use the scientific-schematics skill instead.MediaFără avertismente★ 55,5 K↓ —
- chief-financial-officercbrock84/headcountAn agent organization structured as a company — 15+ departments, 125+ skills, each independently installable, citing the standards and regulators that settle the question. Runs in Claude Code and ChatGPT.FinanțeFără avertismente★ 2,5 K↓ —
- analytical-method-validationK-Dense-AI/scientific-agent-skillsPlans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.TestareFără avertismente★ 55,5 K↓ —
- qiime2-ampliconK-Dense-AI/scientific-agent-skillsProcesses paired-end 16S amplicon reads into QIIME 2 ASVs and taxonomy with retained artifact provenance. Checks paired FASTQ manifests, primer orientation diagnostics, predicted post-trimming overlap, sample IDs, runtime versions and read retention, and guides selection of compatible taxonomic classifiers.AlteleFără avertismente★ 55,5 K↓ —
- bulk-rnaseqK-Dense-AI/scientific-agent-skillsPrepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.ȘtiințăFără avertismente★ 55,5 K↓ —
- release-helperSahir619/fable-methodEnsures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.RedactareFără avertismente★ 2,3 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★ 55,5 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★ 55,5 K↓ —
- behavioral-marketingcbrock84/headcountApplies decision science and cognitive bias research to marketing and product decisions — how people actually choose under uncertainty, and how framing, defaults, sequencing, and social context change behavior. Use this to diagnose why a well-argued offer is not converting, to structure choices and pricing presentation, to design an experience around how attention and memory work, or to pressure-test whether a persuasion tactic is legitimate or manipulative.MarketingFără avertismente★ 2,5 K↓ —
- what-if-oracleK-Dense-AI/scientific-agent-skillsSupports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.TestareFără avertismente★ 55,5 K↓ —
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Datenschutzrecht. Route: output-waehlen.AlteleFără avertismente★ 1,8 K↓ —
- ink-custom-brush-builderNouandroid/skillsCreates custom BrushFamily definitions for an Android app using Jetpack Ink (androidx.ink 1.1.0-alpha03 and higher). Use this skill when configuring custom BrushTip shapes, adding pressure, tilt, speed, or noise sensitivity using BrushBehavior node graphs, creating multi-coat layered brushes, applying tiling or particle stamping textures, configuring SlidingWindowModel input smoothing, or serializing brushes. Delivers complete Kotlin BrushFamily, BrushCoat, BrushTip, BrushPaint, and BrushBehavior implementations. Don't use for View-based (XML) inking, Compose drawing surface setup, or stock brush selection. For Compose drawing surface setup, InProgressStrokes wet and dry rendering, eraser, or persistence, suggest the ink-app-builder skill.OficialMediaFără avertismente★ 10,1 K↓ —
- performance-managementcbrock84/headcountRuns performance systems that change behavior — expectations, feedback, review cycles, calibration, and handling underperformance. Use this to design or fix a review process, run calibration, write or coach on feedback, address sustained underperformance, or work out why reviews consume weeks and change nothing.DesignFără avertismente★ 2,5 K↓ —
- lead-capturecbrock84/headcountConverts anonymous traffic into known contacts — lead magnets, gated content, free tools, popups, and the forms behind them. Use this to design or improve a lead magnet, plan a free tool, add or fix popups and overlays, improve form conversion, or decide what is worth gating and what should stay open.DesignFără avertismente★ 2,5 K↓ —
- founder-marketingJakeschincariol/founder-skillYour marketing director. Turns the buyer panel and the competitor map into positioning, the channels the target customer actually uses, a 30-day launch campaign with dated posts and ads, the first ten hooks, a budget split and the numbers to watch. Every message answers an objection real or simulated buyers raised. Use when the user says "how do I market this", "marketing plan", "launch campaign", "how do I get customers", "where do I advertise", "write my ads", or "positioning".MarketingFără avertismente★ 2,3 K↓ —
- data-governancecbrock84/headcountEstablishes ownership, definitions, quality, access, and lineage for the organization's data. Use this when metrics disagree between teams, when nobody knows which dataset is authoritative, when setting up data ownership or access policy, when data quality is unreliable, or before opening a dataset to a wider audience.AlteleFără avertismente★ 2,5 K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Produkthaftung und Produktrecht.AlteleFără avertismente★ 1,8 K↓ —
- blog-cannibalizationAgriciDaniel/claude-blogDetect keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports a free local mode (file analysis) and a paid DataForSEO API mode that runs only after the user approves the call count. Outputs a severity-scored report with merge or differentiate recommendations. Use when the user says "cannibalization", "keyword overlap", "competing pages". Not a site audit (blog-audit) or cluster planning (blog-cluster); it changes no files or redirects.RedactareFără avertismente★ 2,6 K↓ —
- pricing-and-packagingcbrock84/headcountSets price, structures packages and tiers, and designs the monetization surfaces that carry them — upgrade paths, paywalls, and offer construction. Use this to set or change pricing, design or restructure tiers, choose a pricing metric, build an offer, design upgrade prompts and paywalls, or evaluate whether a pricing change is safe to make.DesignFără avertismente★ 2,5 K↓ —
- pathogen-variant-surveillanceK-Dense-AI/scientific-agent-skillsQueries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.ȘtiințăFără avertismente★ 55,5 K↓ —
simulation-study
pedrohcgs/claude-code-my-workflow
ProductivitateActualizat 27 sept. 2026
De la autor
Scaffold and run a reproducible Monte Carlo simulation study in R — a declared assumption regime, a parameterized DGP, an estimator grid, a seeded replication loop, and a summary of bias, RMSE, empirical SE, coverage, size/power with Monte Carlo standard errors. Use when the user says "run a Monte Carlo simulation", "simulation study", "check the bias/coverage of an estimator", "compare estimators in simulation", "size and power simulation", "Monte Carlo experiment", or wants to demonstrate an estimator's finite-sample properties. Produces a numbered R script in `scripts/R/` and saves per-replication raw results + a summary table to `output/`.
Instalare
npx skills add pedrohcgs/claude-code-my-workflow --skill simulation-study -a claude-code
Se instalează în .claude/skills/simulation-study/ · 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
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
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De ce 89
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Proveniență79
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Licență100
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- SKILL.md