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.
45,604 skills from 2,205 repositories · updated 23 hours ago
44,573 skills
- tiktok-automationdavepoon/buildwithclaudeAutomate TikTok tasks via Rube MCP (Composio): upload/publish videos, post photos, manage content, and view user profiles/stats. Always search tools first for current schemas.MediaNo warnings★ 3.7K↓ —
- gsd:sketchdavepoon/buildwithclaudeSketch UI/design ideas with throwaway HTML mockups, or propose what to sketch next (frontier mode)DesignNo warnings★ 3.7K↓ —
- data-storytellingforyourhealth111-pixel/Vibe-SkillsTransform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.DataNo warnings★ 3.8K↓ —
- trello-automationdavepoon/buildwithclaudeAutomate Trello boards, cards, and workflows via Rube MCP (Composio). Create cards, manage lists, assign members, and search across boards programmatically.OtherNo warnings★ 3.7K↓ —
- speckit-implementforyourhealth111-pixel/Vibe-SkillsExecute all tasks from the task breakdown to build the feature. Use after task generation to systematically implement the planned solution following TDD approach where applicable.PlanningNo warnings★ 3.8K↓ —
- 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↓ —
- pr-gardeningpaperclipai/paperclipDiscover the pull requests this Paperclip instance opened (never community contributions), report what each is for and how confident we are that it is merge-ready, and automatically drive the non-ready ones back to green with /prepare-paperclip-pr — without ever merging.OtherNo warnings★ 107.1K↓ —
- programmatic-seonowork-studio/notfair-pluginProgrammatic SEO planning and audit: building or evaluating large sets of template-generated pages that target long-tail query patterns (e.g. "[service] in [city]", "[product] vs [product]", "[tool] for [use-case]"). Covers data-source and template design, thin/duplicate-content and doorway-page risks, per-page uniqueness and value thresholds, internal linking and hubs, indexation management (publish vs. noindex), and scaling without a manual action. Use whenever the user wants to generate many pages from a template/dataset, build location/comparison/use-case pages at scale, or asks why generated pages aren't indexing. Trigger on: "programmatic SEO", "pSEO", "generate pages at scale", "templated pages", "location pages at scale", "comparison pages", "[city] pages", "my generated pages aren't indexed", "doorway pages", "scale content". For one-off content use /content-writer; for keyword discovery use /keyword-research.MarketingNo warnings★ 4.1K↓ —
- kiro-spec-requirementsgotalab/cc-sddGenerate EARS-format requirements based on project description and steering context. Use when generating requirements from project description.PlanningNo warnings★ 3.7K↓ —
- etf-premiumhimself65/finance-skillsCalculate an ETF's premium or discount to NAV from Yahoo Finance data (yfinance), compare or screen ETFs by premium, explain why a gap exists, and decompose a sudden ETF move into NAV-driven vs structural components (dealer gamma exposure, blocked AP arbitrage, sentiment). Use this skill whenever the user asks whether an ETF trades above or below NAV, compares ETF premiums or discounts, screens for the biggest ones, asks about ETF arbitrage or premium convergence, or wants to know why an ETF jumped or diverged from its holdings — including gamma squeezes, dealer gamma exposure (GEX), and blocked creation/redemption. Especially relevant for leveraged, inverse, international, bond, commodity, and crypto ETFs (IBIT, BITO, HYG, KWEB).FinanceNo warnings★ 3.5K↓ —
- paid-ads-chatgptnowork-studio/notfair-pluginPlan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. Use for ChatGPT advertising, OpenAI ads, conversational ad concepts, ChatGPT campaign plans, or performance reviews from a verified export.MarketingNo warnings★ 4.1K↓ —
- speckit-analyzeforyourhealth111-pixel/Vibe-SkillsPerform cross-artifact consistency analysis across spec.md, plan.md, and tasks.md. Use after task generation to identify gaps, duplications, and inconsistencies before implementation.PlanningNo warnings★ 3.8K↓ —
- hormuz-straithimself65/finance-skillsCheck the live status of the Strait of Hormuz from the Hormuz Strait Monitor dashboard: open, restricted, or closed status, tanker transits vs normal, stranded vessels, Brent price impact, war-risk insurance levels, cargo throughput, tanker freight rates, diplomatic developments, and global trade impact. Use this skill whenever the user asks about the Strait of Hormuz or the Persian Gulf in the context of oil, shipping, or geopolitical risk — whether Hormuz is open, chokepoint or transit disruption, Gulf tanker traffic, war-risk premiums, Middle East shipping routes, or energy supply-chain risk.ProductivityNo warnings★ 3.5K↓ —
- skill-article-outlineZJU-REAL/Easel生成长文大纲：基于搜索分析生成 H2/H3 标题结构、段落字数目标、图表位置和 FAQ 规划，适用于公众号文章、知乎专栏、博客。 当用户说"文章大纲""长文结构""公众号大纲""知乎回答框架""写作提纲""文章框架""H2/H3 结构"时使用。WritingNo warnings★ 4.1K↓ —
- trailmark-variant-neighborhoodtrailofbits/skillsExpands one confirmed or suspected vulnerability into a Trailmark graph neighborhood of variant candidates by finding sibling functions, shared callers and callees, common sensitive sinks, common entrypoint paths, interface implementations, override relationships, type/reference neighbors, and structurally similar nodes. Use after one issue is found to seed variant-analysis, semgrep-rule-creator, static-analysis, or manual review with graph-derived candidate locations.SecurityNo warnings★ 7.8K↓ —
- brand-guidelinesdavepoon/buildwithclaudeApplies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.DesignNo warnings★ 3.7K↓ —
- sepiaNanako0129/sepiaMake AI-generated writing read as human-written, in fiction and in professional prose. Repairs the narrative architecture of fiction and stories (based on StoryScope, arXiv:2604.03136); routes professional text through domain rules for release notes, announcements, PR and issue replies, code-review comments, incident postmortems, tickets, work orders, technical articles, blog posts, and long-form journalism. Four operations - write, review (diagnose AI tells without editing), refactor (minimal in-place edits), recreate (full rewrite). Use when asked to humanize, de-AI, unslop, or strip AI flavor from any text; when writing or revising any of these document types; or whenever output must not read as machine-written.ScienceNo warnings★ 3.5K↓ —
- hyperliquid-readerhimself65/finance-skillsRead Hyperliquid (app.hyperliquid.xyz) perp and spot market data through opencli and Hyperliquid's public info API: mark, oracle, and mid prices, 24h change, funding rates (hourly and annualized APR), open interest, volume, the L2 order book, OHLCV candles, funding history, and cross-venue funding comparisons (Hyperliquid vs Binance vs Bybit) for funding arbitrage. Use this skill whenever the user mentions Hyperliquid (HL, HL DEX, hyperliquid.xyz) or asks about its perps, spot pairs such as PURR, funding, open interest, order book, or candles. Read-only market data: no account, order, or transfer operations.EngineeringNo warnings★ 3.5K↓ —
- skill-profile-managerZJU-REAL/Easel管理账号画像全生命周期：创建空白画像、编辑六维字段、更新记忆、切换、导出和对比。 当用户说“新建/编辑/更新/切换/导出/对比画像、写进画像记忆”时使用。 首次从社媒数据生成画像用 skill-profile-builder；只提炼语言风格用 skill-voice-builder；品牌首次入驻引导用 skill-brand-onboarding。OtherNo warnings★ 4.1K↓ —
- document-skillsforyourhealth111-pixel/Vibe-SkillsUmbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.DocumentsNo warnings★ 3.8K↓ —
- skill-campaign-plannerZJU-REAL/Easel活动/营销策划（国内本地化）：为节日营销、电商大促（618/双11/年货节）、新品发布、活动造势 制定完整方案——目标拆解、营销节奏（预热-爆发-返场）、多平台内容矩阵、互动玩法、KOL 分层、 预算分配、风险合规、效果指标。当用户说"营销方案""活动策划""大促方案""618/双11 怎么做" "节日营销""新品发布方案""造势""campaign""营销节奏""怎么搞活动"时使用。MarketingNo warnings★ 4.1K↓ —
- kiro-verify-completiongotalab/cc-sddVerify completion and success claims with fresh evidence. Use before claiming a task is complete, a fix works, tests pass, or a feature is ready for GO.TestingNo warnings★ 3.7K↓ —
- ulw-loopcode-yeongyu/oh-my-openagentA goal-like loop that decomposes work into systematic, evidence-bound ultrawork steps. Use when the user wants a goal loop or durable, checkpointed execution.OtherNo warnings★ 70.3K↓ —
- golang-swaggersamber/cc-skills-golangGolang OpenAPI/Swagger documentation with swaggo/swag — annotation comments (@Summary, @Param, @Success, @Router, @Security), swag init code generation, framework integrations (gin, echo, fiber, chi, net/http), security definitions (Bearer/JWT, OAuth2, API key), and struct tags (swaggertype, enums, example, swaggerignore). Apply when adding or maintaining Swagger/OpenAPI docs in a Go project, or when the codebase imports github.com/swaggo/swag, github.com/swaggo/gin-swagger, github.com/swaggo/echo-swagger, github.com/swaggo/http-swagger, or github.com/swaggo/files.SecurityNo warnings★ 3.6K↓ —
tao-finetune-kumo-anomaly
NVIDIA/skills
OtherUpdated 2 days ago
From the author
Kumo-Anomaly — diffusion-based anomaly detection and fine-tuning for multivariate time series. Use when the user asks to "fine-tune Kumo-Anomaly", "run Kumo-Anomaly inference", "detect anomalies with diffusion", "time series anomaly detection", "finetune Kumo-Anomaly", "use perform_anomaly_analysis_with_diffusion", "automl Kumo-Anomaly", "hyperparameter search Kumo-Anomaly", "hyperparameter optimization" or mentions "curriculum_medium.yaml", "final_model.pth", "kumo-anomaly", "sdk/anomaly_analysis", or "TSDiffuser_Generic".
Install
npx skills add NVIDIA/skills --skill tao-finetune-kumo-anomaly -a claude-code
Installs to .claude/skills/tao-finetune-kumo-anomaly/ · 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 onlyUses the networkLicence: APACHE-2.0
Safety checks on SKILL.md
No warnings.
Why 90
Security100
Provenance83
Maintenance100
Licence100
Adoption57
Files (12)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- evals/evals.json
- references/automl.md
- references/skill_info.yaml
- references/spec_template_inference_hpo.yaml
- references/spec_template_train.yaml
- schemas/inference_hpo.schema.json
- schemas/train.schema.json
- skill-card.md
- skill.oms.sig