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.
47,966 skills from 2,309 repositories · updated 11 hours ago
46,854 skills
- chronologieKlotzkette/claude-fuer-deutsches-rechtFür Sachverhalts-Chronologie: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Chronologie mit Beleg- und Widerspruchsmatrix.OtherNo warnings★ 1.8K↓ —
- 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★ 55.4K↓ —Also in 1 other repo
- stipulatioKlotzkette/claude-fuer-deutsches-rechtFür Stipulatio: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- org-designcbrock84/headcountDesigns how an organization is structured — reporting lines, team boundaries, spans and layers, role definition, and workforce planning against the strategy. Use this to structure a new team, restructure an existing one, resolve unclear ownership between teams, plan headcount, or diagnose why a team underperforms for structural rather than individual reasons.DesignNo warnings★ 2.5K↓ —
- service-level-managementcbrock84/headcountDefines and manages service levels — setting targets that reflect what customers need, measuring honestly, and handling breaches. Use this to write or negotiate an SLA, decide what to measure and at what threshold, respond to a missed service level, or work out why a service that meets its targets still has unhappy customers.WritingNo warnings★ 2.5K↓ —
- cashburnKlotzkette/claude-fuer-deutsches-rechtFür Cash Burn und Insolvenzfrühwarnung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- pennylaneK-Dense-AI/scientific-agent-skillsBuilds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for open-system dynamics use qutip.PlanningNo warnings★ 55.4K↓ —Also in 1 other repo
- 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.ScienceNo warnings★ 55.4K↓ —
- 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.ScienceNo warnings★ 55.4K↓ —
- geopandasK-Dense-AI/scientific-agent-skillsGuidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.EngineeringNo warnings★ 55.4K↓ —Also in 1 other repo
- bonusKlotzkette/claude-fuer-deutsches-rechtFür Bonus und leistungsbezogene Vergütung im Handelsvertretervertrag: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- zhengxi-viewslyra81604/zhengxi-views郑希观点库——基于易方达基金经理郑希 2012–2026 年全部公开观点原文语料，外加从语料蒸馏、有本人原话佐证的郑希投资方法的可溯源 research skill。能做： (1) 溯源问答——他怎么看 AI算力/光通信/新能源/半导体/ROE 等，引用其原话作答； (2) 讲解他的投资方法/框架/选股逻辑；(3) 前瞻应用——用他的方法分析当下任意主题/行业/个股，语料没谈过也能据框架推演； (4) 风格化点评——用他季报/手记的口吻写市场点评、季度展望； (5) 言行对照——用他全部基金真实数据（季度持仓/净值/业绩/规模/任职回报）核对"说的"与"买的"，或答他的业绩/重仓/规模； (6) 全市场查询对比——内置约 2.7 万只基金列表，按需抓任意基金真实数据做查询或与郑希对比； (7) 郑希框架评分——给一只基金按他的方法打分（多像郑希会买的）。 When the user mentions 郑希/易方达郑希/zhengxi, asks his view on a sector/stock/theme, his 投资方法/框架/选股/风格/持仓/业绩/净值/规模, wants to apply his approach, a commentary 用郑希口吻, to check words vs holdings, or to look up/compare/score ANY China mutual fund (任意基金/某基金经理/同类对比/给基金打分)——use this skill, even if they don't say "skill", even if the topic isn't in his corpus (fall back to his method). 引用忠于原文、不杜撰；推演与原话区分。研究学习辅助，非投资建议。ScienceNo warnings★ 1.8K↓ —
- 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.DesignNo warnings★ 63.2K↓ —
- 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.ScienceNo warnings★ 55.4K↓ —
- 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.TestingNo warnings★ 55.4K↓ —
- scientific-brainstormingK-Dense-AI/scientific-agent-skillsFacilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.ScienceNo warnings★ 55.4K↓ —
- 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.MediaNo warnings★ 55.4K↓ —
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestingNo warnings★ 55.4K↓ —
- get-available-resourcesK-Dense-AI/scientific-agent-skillsDetects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.TestingNo warnings★ 55.4K↓ —
- 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.ScienceNo warnings★ 55.4K↓ —
- 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.MediaNo warnings★ 55.4K↓ —
- network-administrationcbrock84/headcountDesigns and operates the corporate network — segmentation, remote access, wireless, DNS and addressing, and diagnosing network problems. Use this to segment a network, set up or fix remote access, diagnose intermittent connectivity, plan addressing or DNS, or assess whether the network's trust assumptions still hold.PlanningNo warnings★ 2.5K↓ —
- 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.DevOpsNo warnings★ 55.4K↓ —
- scvi-toolsK-Dense-AI/scientific-agent-skillsFits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.OtherNo warnings★ 55.4K↓ —
dsfa-erstellung
Klotzkette/claude-fuer-deutsches-recht
OtherUpdated Oct 23, 2026
From the author
Für DSFA – Datenschutz-Folgenabschätzung Art. 35 DSGVO: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
Install
npx skills add Klotzkette/claude-fuer-deutsches-recht --skill dsfa-erstellung -a claude-code
Installs to .claude/skills/dsfa-erstellung/ · 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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Files (1)
- SKILL.md