Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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mui-docs
Use this to read the MUI (Material UI) documentation.
majiayu000/claude-skill-registry 163
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bio-stats-ml-reporting
Aggregate results, train ML models, and produce reports with validated references.
majiayu000/claude-skill-registry 163
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agentuity-cli-cloud-eval-run-get
Get details about a specific eval run. Requires authentication. Use for Agentuity cloud platform operations
majiayu000/claude-skill-registry 163
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samara
majiayu000/claude-skill-registry 163
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blazor-framework
majiayu000/claude-skill-registry 163
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comprehensive-system-analyzer
Deep comprehensive system status analyzer that provides honest truth reporting about entire Pomo-Flow application health, performance, and integrity
majiayu000/claude-skill-registry 163
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food-order
majiayu000/claude-skill-registry 163
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model-comparison-tool
Use when asked to compare multiple ML models, perform cross-validation, evaluate metrics, or select the best model for a classification/regression task.
majiayu000/claude-skill-registry 163
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klingai-pricing-basics
Manage understand Kling AI pricing, credits, and cost optimization. Use when budgeting or optimizing
costs for video generation. Trigger with phrases like 'kling ai pricing', 'klingai credits',
'kling ai cost', 'klingai budget'.
majiayu000/claude-skill-registry 163
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gemini-extension-development
Expert guide for building and managing Gemini CLI Extensions. Covers extension anatomy, GEMINI.md context, commands, MCP integration, and publishing. Use when creating Gemini extensions, linking local extensions, packaging MCP servers, or installing extensions from GitHub. Delegates to gemini-cli-docs.
majiayu000/claude-skill-registry 163
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conversation-memory
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
majiayu000/claude-skill-registry 163
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onboarding
idp-serverプロジェクト初心者向けのオンボーディングガイド。プロジェクト全体像、学習ロードマップ、開発環境構築、最初のコントリビューションまでをサポート。
majiayu000/claude-skill-registry 163
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design-components
[デザイン] 3. 静的UI骨格 → Layout/Component を抽出して分離
majiayu000/claude-skill-registry 163
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aws-cloudformation-cloudfront
AWS CloudFormation patterns for CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring multiple origins, implementing caching strategies, managing custom domains with ACM, configuring WAF, and optimizing performance.
majiayu000/claude-skill-registry 163
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mindmap-skill
Maintain and evolve interactive mind maps generated from OPML outlines and XML palettes.
majiayu000/claude-skill-registry 163
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retention-analysis
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
majiayu000/claude-skill-registry 163
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atlas14-spatial-variance
Analyze spatial variability of NOAA Atlas 14 precipitation frequency estimates
within HEC-RAS model domains using intelligent extent-based downloading.
Helps determine whether uniform rainfall assumptions are appropriate for
rain-on-grid modeling by calculating min/max/mean/range statistics within
2D flow areas or project extents.
Uses NOAA CONUS NetCDF with HTTP byte-range requests for 99.9% data reduction
compared to traditional state-level ZIP downloads.
Primary sources:
- ras_commander/precip/CLAUDE.md (lines 118-629) - Complete workflows
- ras_commander/precip/Atlas14Grid.py - API reference
- ras_commander/precip/Atlas14Variance.py - Variance analysis API
- examples/725_atlas14_spatial_variance.ipynb - Working demonstration
majiayu000/claude-skill-registry 163
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responsive-images
Implement performant responsive images with srcset, sizes, lazy loading, and modern formats (WebP, AVIF). Covers aspect-ratio for CLS prevention, picture element for art direction, and fetchpriority for LCP optimization.
Use when: adding images to pages, optimizing Core Web Vitals, preventing layout shift, implementing art direction, or converting to modern formats.
majiayu000/claude-skill-registry 163
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learning-impact-measurement
impact-measurement for measuring learning effectiveness and business impact.
majiayu000/claude-skill-registry 163
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nextjs-performance-optimizer
Use this skill whenever the user wants to analyze, improve, or enforce performance best practices in a Next.js (App Router) + TypeScript + Tailwind + shadcn/ui project, including bundle size, data fetching, caching, streaming, images, fonts, and client/server boundaries.
majiayu000/claude-skill-registry 163
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accept-pr
Land one PR end-to-end (changelog + thanks, lint, merge, back to main).
majiayu000/claude-skill-registry 163
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browser-task-and-automation-and-delegation
【强制】所有浏览器操作必须使用本技能，禁止在主对话中直接使用 mcp__chrome-devtools 工具。触发关键词：打开/访问/浏览网页、点击/填写/提交表单、截图/快照、性能分析、自动化测试、数据采集/爬取、网络模拟。本技能通过 chrome-devtools-expert agent 执行浏览器操作，避免大量页面快照、截图、网络请求数据污染主对话上下文。
majiayu000/claude-skill-registry 163
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discover-capabilities
Use this at session start to discover what CodeCompass can do. Read .ai/capabilities.json for module map (5 domains, 21+ modules) instead of manual Grep/Glob. Apply when: (1) planning tasks, (2) user asks 'What can CodeCompass do?', (3) before implementing features
majiayu000/claude-skill-registry 163
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Computer Vision
Implement computer vision tasks including image classification, object detection, segmentation, and pose estimation using PyTorch and TensorFlow
majiayu000/claude-skill-registry 163