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 7 hours ago
49,492 skills
- expo-uisickn33/agentic-awesome-skillsBuild native UI with the @expo/ui package: real SwiftUI on iOS and Jetpack Compose on Android rendered from React in an Expo or React Native app.DesignNo warnings★ 49.1K↓ —
- remote-from-slackcodeaholicguy/ai-devkitAI DevKit · Connect the current agent session to an available Slack channel bridge.OtherNo warnings★ 1.7K↓ —
- seabornsickn33/agentic-awesome-skillsSeaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.EngineeringNo warnings★ 49.1K↓ —
- ontology-term-resolutionK-Dense-AI/scientific-agent-skillsResolves free-text scientific labels to ontology term IDs and validates existing CURIEs against the EBI Ontology Lookup Service (OLS4). Also looks up prefixes in Bioregistry, resolves compact identifiers via Identifiers.org, maps lab shorthand with ZOOMA, and builds Ontobee term pages. Use whenever an ontology identifier must be produced or checked - annotating tissue, cell type, disease, phenotype, assay, chemical, organism, sex, or developmental stage fields; preparing metadata for GEO, ENA, BioSamples, CELLxGENE, HCA, or ISA-Tab submission; auditing a metadata table of term IDs; checking whether a term is obsolete and what replaced it; or deciding HPO vs HP. Triggers include "ontology term", "ontology ID", "CURIE", "controlled vocabulary", "UBERON", "CL:", "MONDO", "HPO", "EFO", "ChEBI", "NCBITaxon", "GO term", "PATO", "Zooma", "Bioregistry", "Identifiers.org", "Ontobee", "annotate this tissue/cell type/disease", and any request to emit or verify an identifier shaped like PREFIX:0001234.ScienceNo warnings★ 56.1K↓ —
- lockup-daysKlotzkette/claude-fuer-deutsches-rechtFür Lock-up Days: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- dev-implementationcodeaholicguy/ai-devkitAI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.DesignNo warnings★ 1.7K↓ —
- backupLeoYeAI/agent-master-skillsBackup and restore openclaw configuration, skills, commands, and settings. Sync across devices, version control with git, automate backups, and migrate to new machines.EngineeringNo warnings★ 2.2K↓ —
- aktenzeichenKlotzkette/claude-fuer-deutsches-rechtFür Aktenzeichen und Verknüpfungen: ordnet Akte, Belege und Lücken; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- gdrive_synthesizeKaelio/ktxSynthesize durable KTX wiki pages from staged Google Drive document pulls. Load when a WorkUnit contains Google Doc raw files from `docs/**`.OtherNo warnings★ 1.6K↓ —
- translatefeiskyer/claude-code-settingsTranslate English or Japanese tech articles into natural, fluent Chinese. Use whenever the user asks for Chinese translation, says "translate to Chinese" or "翻译", or provides English/Japanese content (pasted text or a file) to convert into Chinese. Chinese output only — not for translating into other languages.OtherNo warnings★ 1.7K↓ —
- 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★ 56.1K↓ —
- 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★ 56.1K↓ —
- scenario-moderationscenario-labs/skillsUse when a Scenario generation is blocked, refused, or returns a moderation or sensitive-content error, when a video is rejected after rendering or its audio track is flagged, when an output is flagged for likeness to a real person or for IP and copyright detection, when the same prompt passes on one model and fails on another, or when a team's own characters, weapons, or props get flagged. Keywords: blocked prompt, content moderation, refused generation, provider filter, false positive.MediaNo warnings★ 2.2K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Energierecht.OtherNo warnings★ 1.8K↓ —
- scenario-luma-videoscenario-labs/skillsUse when generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.MediaNo warnings★ 2.2K↓ —
- remote-from-telegramcodeaholicguy/ai-devkitAI DevKit · Connect the current agent session to an available Telegram channel bridge.OtherNo warnings★ 1.7K↓ —
- pydicomK-Dense-AI/scientific-agent-skillsReads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.WritingNo warnings★ 56.1K↓ —Also in 2 other repos
- coauthor-briefpedrohcgs/claude-code-my-workflowGenerate a co-author / collaborator handoff brief for a multi-author, multi-machine project — summarizing what changed since the last brief (git delta), the current state of each artifact (manuscript, analysis, slides), open questions, how to reproduce locally, and any restricted-data access steps. Use when user says "coauthor brief", "handoff brief", "bring my coauthor up to speed", "what changed since last week", "onboard a collaborator", "write a handoff for [name]", or before sending a co-author the repo. NOT a commit or a checkpoint — it is the cross-machine, cross-person summary `meta-governance.md` only partially covers.DocumentsNo warnings★ 1.7K↓ —
- 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★ 56.1K↓ —
- 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★ 56.1K↓ —
- zeitleisteKlotzkette/claude-fuer-deutsches-rechtFür Zeitleiste des Datenschutzvorfalls — minutiöse Rekonstruktion: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- scenario-luma-imagescenario-labs/skillsUse when generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.MediaNo warnings★ 2.2K↓ —
- dev-commitcodeaholicguy/ai-devkitAI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.EngineeringNo warnings★ 1.7K↓ —
- scanpyK-Dense-AI/scientific-agent-skillsPerforms Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or SingleCellExperiment RDS conversion to h5ad. Applies to established exploratory scRNA-seq workflows with explicit count and expression provenance; complementary skills cover scvi-tools models and AnnData format details.MarketingNo warnings★ 56.1K↓ —Also in 2 other repos
seaborn
K-Dense-AI/scientific-agent-skills
DataUpdated 3 days ago
From the author
Creates 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.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill seaborn -a claude-code
Installs to .claude/skills/seaborn/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (Custom or unclear) does not let us redistribute its files. The install commands fetch them from GitHub instead.
What it can touch
Instructions onlyUses the networkLicence: Custom or unclear
Safety checks on SKILL.md
No warnings.
Why 89
Security100
Provenance95
Maintenance100
Licence45
Adoption73
Files (8)
- SKILL.md
- references/examples.md
- references/function_reference.md
- references/grids_and_levels.md
- references/objects_interface.md
- references/palettes_and_theming.md
- references/patterns_and_troubleshooting.md
- references/plotting_functions.md