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 4 hours ago
49,492 skills
- tao-generate-anomaliesNVIDIA/skillsFull PAIDF AnomalyGen pipeline — fine-tune on a new anomaly dataset, generate synthetic anomaly images (SDG), evaluate quality (nn_score), and search per-sample (guidance, crop_ratio) parameters. Three modes: full (Phase 0→7: finetune then generate), finetune_only (Phase 0→1: train only), inference_only (Phase 0, 2→7: generate from an existing checkpoint). Use when the user asks to "fine-tune AnomalyGen", "generate anomaly images", "run PAIDF SDG", "evaluate SDG output quality", "run per-sample search", or run any part of the AnomalyGen pipeline, even if they only mention one phase.OtherNo warnings★ 3.9K↓ —
- tao-train-reidNVIDIA/skillsPerson re-identification (ReID). Learns discriminative embeddings to match the same person across different camera views, based on metric learning. Use when training, evaluating, exporting, or running inference for a TAO person re-identification model. Trigger phrases include "train ReID", "person re-identification", "cross-camera person matching", "ReID embeddings", "person re-id".OtherNo warnings★ 3.9K↓ —
- instrument-data-to-allotropeanthropics/knowledge-work-pluginsConvert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.OfficialDataNo warnings★ 34.7K↓ —
- create-formal-verification-skillbacknotprop/pstackGenerate a project-local skill that formally verifies the code where a bug costs the most and tests reach the least, in any language, with whichever verification tool fits. Use for /create-formal-verification-skill, "model-check this race", "prove this invariant", or when concurrency, retries, state machines, parsers, or unsafe code need more than tests.TestingNo warnings★ 3.5K↓ —
- offensive-fuzzingSnailSploit/Claude-RedPractical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers, network protocols, kernel drivers, EDR engines, embedded firmware, or language runtimes.WritingNo warnings★ 10.3K↓ —
- finta-rate-limitsjeremylongshore/tons-of-skills-marketplaceUnderstand Finta usage limits and plan tiers. Trigger with phrases like "finta limits", "finta plan limits".PlanningNo warnings★ 2.9K↓ —
- cuboid-carouselheygen-com/hyperframesA chain of bevelled cuboids rides a travelling wave as a content carousel. HyperFrames block, 1920×1080, 6.666666666666667s, 40 variables.OfficialOtherNo warnings★ 78.7K↓ —
- template-skillanthropics/skillsReplace with description of the skill and when Claude should use it.OfficialOtherNo warnings★ 187.3K↓ —Also in 9 other repos
- keyword-researchaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data. Not for competitor-relative coverage gaps — use content-gap-analysis. 关键词研究/内容选题ScienceNo warnings★ 3.1K↓ —
- LQF_Machine_Learning_Expert_Guideforyourhealth111-pixel/Vibe-SkillsLQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling, prediction, training, classification, regression, clustering, deep learning, neural network, model evaluation, feature engineering, hyperparameter tuning, overfitting, underfitting, baseline, ablation study, critique my approach, review my model, is this a good idea, should I use, what's wrong with, evaluate my solution, challenge my assumptions, discuss my approach Engages in critical discussion with minimum 3 rounds of iterative refinement. Challenges both user proposals and own suggestions with fact-based critique. Demands evidence and baselines before accepting solutions.EngineeringNo warnings★ 3.8K↓ —
- tao-train-mask-auto-labelNVIDIA/skillsMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".OtherNo warnings★ 3.9K↓ —
- stakeholder-updatejeremylongshore/tons-of-skills-marketplaceCreate and review stakeholder status updates, progress reports, and executive summaries. Use when the user needs to write concise upward communication. Trigger with "stakeholder update", "status update", "progress report", "update leadership", "weekly update", or "executive summary".WritingNo warnings★ 2.9K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanningNo warnings★ 1.6K↓ —
- account-based-marketingcbrock84/headcountConcentrates marketing and sales effort on a named set of accounts rather than on volume — qualifying whether the model fits your economics at all, building the account list and the buying group inside each, tiering effort against account value, coordinating so the account experiences one campaign rather than several, and measuring account progression instead of leads. Use this to decide whether to run an account-based program, build one, or work out why an existing one produces activity and no pipeline.MarketingNo warnings★ 2.6K↓ —
- portaljs-add-dcatdatopian/portaljsMake a PortalJS portal harvestable by national/EU/US open-data portals — emit standards-compliant DCAT catalog feeds (DCAT 2/3, DCAT-AP, DCAT-US, national profiles) in JSON-LD, Turtle, and RDF/XML at build, with autodiscovery and per-profile conformance checking. Use when a portal needs to be harvested by data.europa.eu, data.gov, or a national open-data catalog.LegalNo warnings★ 2.4K↓ —
- bumblebeesickn33/agentic-awesome-skillsRun Bumblebee supply-chain inventory and exposure scans on macOS/Linux to detect compromised packages, extensions, and MCP host configs.OtherNo warnings★ 49.1K↓ —
- 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↓ —
- portaljs-architectdatopian/portaljsRecommend a data-portal architecture (storage, compute, catalog, access, hosting, metadata) from stated needs, then hand off to the build skills. The advisory entry point. Use when starting a new data-portal project and the underlying architecture has not yet been decided.PlanningNo warnings★ 2.4K↓ —
- seo-new-keywords-researchzhuyansen/new-term-radarTurn new AI names or unstructured AI market signals into a keyword priority table. For each name it finds the generic search terms downstream of it, screens them for relevance, and checks novelty, demand size and momentum against Google Ads volume and DataForSEO Trends (an estimate of Google search interest), ending in prioritize, watch or skip. Use when the user has new model, product or repository names (or an AI listening report, a batch of posts, a changelog) and asks which keywords to build pages or tools for. Runs the new-term-radar command line; needs an AISA_API_KEY, and a GOANYAPI_API_KEY improves it.ScienceNo warnings★ 2.1K↓ —
- translate-to-quartopedrohcgs/claude-code-my-workflowA ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.TestingNo warnings★ 1.7K↓ —
- blue-ocean-strategywondelai/skillsCreate uncontested market space using value innovation instead of competing head-to-head. Use when the user mentions "blue ocean", "red ocean", "strategy canvas", "ERRC framework", "value innovation", "non-customers", "buyer utility map", "the market is too crowded", "how do we stand out", or "escape the price war". Also trigger when exploring a new market category, or finding underserved or non-customers. Covers the Four Actions Framework, Six Paths, buyer utility map, and value-cost trade-offs. For real strategy formulation and bad-strategy detection, see good-strategy-bad-strategy. For tech adoption strategy, see crossing-the-chasm. For product positioning, see obviously-awesome.OtherNo warnings★ 2.6K↓ —Also in 2 other repos
- nature-figureYuan1z0825/nature-skillsCreate, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.ScienceNo warnings★ 52.2K↓ —
- blogAgriciDaniel/claude-blogFull-lifecycle blog engine with 31 sub-skills, 12 templates, 100-point scoring, and 5 agents. Routes requests to the right sub-skill: writing, rewriting, analysis, outlines, audits, schema, charts, images, repurposing, AI citation SEO, FLOW prompts, topic clusters, and multilingual publishing. Optimized for Google rankings, E-E-A-T, and AI citations. Supports any platform. Use when the user asks to create, revise, analyze, plan, translate, localize, audit, or repurpose blog content, or invokes a /blog subcommand. Do not activate merely because the word "blog" appears in an unrelated coding, theme-debugging, database, log-analysis, or definition request.WritingNo warnings★ 2.6K↓ —
- verkehrsunfallKlotzkette/claude-fuer-deutsches-rechtFür Verkehrsunfall – Haftung, Schaden und Schadensausgleich: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
sentry-load-scale
jeremylongshore/tons-of-skills-marketplace
TestingUpdated 17 hours ago
From the author
Scale Sentry for high-traffic applications handling millions of events per day. Use when optimizing SDK performance at high volume, implementing adaptive sampling, managing quotas and costs at scale, or deploying Sentry across multi-region infrastructure. Trigger with phrases like "sentry high traffic", "scale sentry", "sentry millions events", "sentry high volume", "sentry quota management", "sentry load test".
Install
npx skills add jeremylongshore/tons-of-skills-marketplace --skill sentry-load-scale -a claude-code
Installs to .claude/skills/sentry-load-scale/ · 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: MIT
Safety checks on SKILL.md
No warnings.
Why 90
Security100
Provenance82
Maintenance100
Licence100
Adoption55
Files (7)
- SKILL.md
- references/buffering-and-batching.md
- references/errors.md
- references/examples.md
- references/high-volume-sampling-strategies.md
- references/quota-management-at-scale.md
- references/resource-optimization.md