Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,492 skills from 2,391 repositories · updated 13 hours ago
49,492 skills
- exploratory-data-analysisK-Dense-AI/scientific-agent-skillsPerforms bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.DataNo warnings★ 56.1K↓ —
- clinical-decision-supportK-Dense-AI/scientific-agent-skillsPrepares and validates research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Supports aggregate or synthetic research documentation and traceability, excluding patient care and live clinical operation.ScienceNo warnings★ 56.1K↓ —
- protocolsio-integrationK-Dense-AI/scientific-agent-skillsReads, validates, and safely exports protocols.io data with current official REST/MCP contracts, or creates non-executing mutation plans. The bundled client makes bounded official-host GET requests only with explicit --execute. Use only for tasks explicitly targeting protocols.io or an exact protocols.io protocol version.PlanningNo warnings★ 56.1K↓ —
- 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.TestingNo warnings★ 56.1K↓ —
- nwb-conversionK-Dense-AI/scientific-agent-skillsConverts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.MarketingNo warnings★ 56.1K↓ —
- primer-designK-Dense-AI/scientific-agent-skillsDesigns and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.DesignNo warnings★ 56.1K↓ —
- pkpd-modelingK-Dense-AI/scientific-agent-skillsPharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".OtherNo warnings★ 56.1K↓ —
- open-notebookK-Dense-AI/scientific-agent-skillsOrganizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST API or configuring its local or cloud AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral.MediaNo warnings★ 56.1K↓ —
- threat-modelingcbrock84/headcountIdentifies what could go wrong in a system before it is built or changed — the assets worth attacking, the entry points, the trust boundaries, and the controls that actually address the realistic threats. Use this when designing a feature or system, when a change touches authentication, data handling, payments, or external input, before a security review, or when deciding which security work is worth doing at all.SecurityNo warnings★ 2.6K↓ —
- eval-driven-devgithub/awesome-copilotImprove AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.TestingNo warnings★ 40.8K↓ —
- 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.DocumentsNo warnings★ 56.1K↓ —Also in 1 other repo
- gruen-fehlerkatalogKlotzkette/claude-fuer-deutsches-rechtFür Grün Fehlerkatalog: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- geomasterK-Dense-AI/scientific-agent-skillsSupports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation. Use when processing satellite imagery, aligning coordinate systems and raster grids, accessing STAC catalogs, analyzing geospatial time series, or implementing scientific GIS workflows in Python, R, Julia, JavaScript, C++, Java, Go, or Rust.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- webapp-testinggithub/awesome-copilotToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.TestingNo warnings★ 40.8K↓ —
- pyhealthK-Dense-AI/scientific-agent-skillsBuilds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- 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.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- benefits-realizationcbrock84/headcountEnsures projects deliver the value they were approved on — defining measurable benefits, baselining, tracking after delivery, and honest post-implementation review. Use this to define benefits for a business case, set a baseline, track whether value actually landed, or run a post-implementation review that produces something useful.EngineeringNo warnings★ 2.6K↓ —
- 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.DocumentsNo warnings★ 56.1K↓ —Also in 2 other repos
- product-launchcbrock84/headcountTakes something built and gets it into the market — tiering the launch to match what it actually warrants, sequencing internal readiness before external announcement, preparing sales and support to answer the questions it creates, choosing the date for a reason, and measuring adoption rather than announcement reach. Use this to plan a launch, right-size one that is consuming more than it deserves, work out why a released feature nobody uses was launched loudly, or run the weeks after launch day.PlanningNo warnings★ 2.6K↓ —
- deal-negotiationcbrock84/headcountNegotiates a commercial deal without giving away the terms that matter — preparing your walk-away and theirs, trading concessions rather than conceding them, recognizing the tactics that create false urgency, protecting price by moving other variables, and closing on terms someone can actually deliver. Use this to prepare for a negotiation, respond to a demand mid-deal, work out why discounts keep landing at quarter end, or review terms before they are signed.FinanceNo warnings★ 2.6K↓ —
- 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.ScienceNo warnings★ 56.1K↓ —Also in 2 other repos
- unit-economicscbrock84/headcountEstablishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.MarketingNo warnings★ 2.6K↓ —
- 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.OtherNo warnings★ 1.8K↓ —
- cost-accountingcbrock84/headcountEstablishes what something actually costs — fixed, variable and mixed cost behavior, absorption versus variable costing, job-order, process and activity-based methods, breakeven and operating leverage, and price/volume/mix decomposition. Use this to set a price floor, explain why revenue or margin moved, decide make versus buy, judge whether a product line earns its place, or work out how an allocation basis is distorting a reported margin.FinanceNo warnings★ 2.6K↓ —
impressum-pflicht
Klotzkette/claude-fuer-deutsches-recht
OtherUpdated 19 hours ago
From the author
Für Impressumspflicht (Paragrafen 5. 6 DDG, Paragraf 18 MStV): ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
Install
npx skills add Klotzkette/claude-fuer-deutsches-recht --skill impressum-pflicht -a claude-code
Installs to .claude/skills/impressum-pflicht/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: APACHE-2.0
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