Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering

Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification

Comprehensive review of local uncommitted changes using specialized agents with code improvement suggestions

Comprehensive pull request review using specialized agents

Execute tasks through competitive multi-agent generation, meta-judge evaluation specification, multi-judge evaluation, and evidence-based synthesis

Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection, quality-focused prompting, and meta-judge → LLM-as-a-judge verification

Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation

Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification

Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates

Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation

creates draft task file in .specs/tasks/draft/ with original user intent

Generate ideas in one shot using creative sampling

Implement a task with automated LLM-as-Judge verification for critical steps

Refine, parallelize, and verify a draft task specification into a fully planned implementation-ready task

Systematically fix all failing tests after business logic changes or refactoring

Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first

Systematically add test coverage for all local code changes using specialized review and development agents. Add tests for uncommitted changes (including untracked files), or if everything is commited, then will cover latest commit.

Pause for review every N tasks - selective autonomy pattern

Applies prompt repetition to improve accuracy for non-reasoning LLMs

分析口腔健康数据、识别口腔问题模式、评估口腔健康状况、提供个性化口腔健康建议。支持与营养、慢性病、用药等其他健康数据的关联分析。

分析皮肤健康数据、识别皮肤问题模式、评估皮肤健康状况、提供个性化皮肤健康建议。支持与营养、慢性病、用药等其他健康数据的关联分析。

分析旅行健康数据、评估目的地健康风险、提供疫苗接种建议、生成多语言紧急医疗信息卡片。支持WHO/CDC数据集成的专业级旅行健康风险评估。

Integrate digital health data sources (Apple Health, Fitbit, Oura Ring) and connect to WellAlly.tech knowledge base. Import external health device data, standardize to local format, and recommend relevant WellAlly.tech knowledge base articles based on health data. Support generic CSV/JSON import, provide intelligent article recommendations, and help users better manage personal health data.

Styling and structure conventions for stream-chat-react. Use when adding or editing components, SCSS, or icons in this repo—file layout, styling folder structure, SCSS imports, and icon placement.

Analyze your Claude Code session logs to improve prompt quality, optimize tool usage, and become a better AI-native engineer.

22 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token output.

This is an Elixir umbrella app with multiple sub-apps under `apps/`.

生成、改写并校验 FOFA 查询语句。用于用户提到 FOFA、资产测绘、语法速查、查询语句编写、语句纠错、条件组合优化时。

Capture, index, and reuse project knowledge across sessions.

Create banners using AI image generation. Discuss format/style, generate variations, iterate with user feedback, crop to target ratio. Use when user wants to create a banner, header, hero image, cover image, GitHub banner, Twitter header, or readme banner.

Search domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check domain prices, find domain deals, compare registrars, or search for .ai/.com domains.

Create logos using AI image generation. Discuss style/ratio, generate variations, iterate with user feedback, crop, remove background, and export as SVG. Use when user wants to create a logo, icon, favicon, brand mark, mascot, emblem, or design a logo.

Generate and edit images using Google Gemini 3 Pro Image (Nano Banana Pro). Supports text-to-image, image editing, various aspect ratios, and high-resolution output (2K/4K). Use when user wants to generate images, create images, use Gemini image generation, or do AI image generation.

Search and retrieve content from Reddit. Get posts, comments, subreddit info, and user profiles via the public JSON API. Use when user mentions Reddit, a subreddit, or r/ links.

Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, LinkedIn, and Amazon. Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries.

SEO & GEO (Generative Engine Optimization) for websites. Analyze keywords, generate schema markup, optimize for AI search engines (ChatGPT, Perplexity, Gemini, Copilot, Claude) and traditional search (Google, Bing). Use when user wants to improve search visibility, search optimization, search ranking, AI visibility, ChatGPT ranking, Google AI Overview, indexing, JSON-LD, meta tags, or keyword research.

Search and retrieve content from Twitter/X. Get user info, tweets, replies, followers, communities, spaces, and trends via twitterapi.io. Use when user mentions Twitter, X, or tweets.

Generate a lean AGENTS.md hub file for a repository or area, including recommended topics for detail files.

Generate a deep-dive instruction file about a specific topic for a repository or area.

Generate a concise .instructions.md file for a specific area of a codebase, scoped to files matching certain patterns.

Generate a concise .github/copilot-instructions.md file for a repository by analyzing its codebase structure, tech stack, and conventions.

Review component for accessibility issues

Implement a playbook from its PROMPT specification files. Supports both single-framework (PROMPT-REACT.md, etc.) and 3-framework (PROMPT-3-FRAMEWORKS.md) modes.

This skill helps Claude write secure web applications. Use this when working on any web application or when a user requests a scan or audit to ensure security best practices are followed.

Architecture specialist for software/system design, module and service boundaries, tradeoff analysis, and stakeholder synthesis. Uses context-aware methods such as diagnostic routing, design-twice comparison, ATAM-style risk analysis, CBAM-style prioritization, and ADR-style decision records.

Backend specialist for APIs, databases, authentication with clean architecture (Repository/Service/Router pattern). Use for API, endpoint, REST, database, server, migration, and auth work.

Guide for coordinating PM, Frontend, Backend, Mobile, and QA agents on complex projects via CLI. Use for manual step-by-step coordination and workflow guidance.

Database specialist for SQL, NoSQL, and vector database modeling, schema design, normalization, indexing, transactions, integrity, concurrency control, backup, capacity planning, data standards, anti-pattern review, and compliance-aware database design. Use for database, schema, ERD, table design, document model, vector index design, RAG retrieval architecture, migration, query tuning, glossary, capacity estimation, backup strategy, database anti-pattern remediation work, and ISO 27001, ISO 27002, or ISO 22301-aware database recommendations.

Bug diagnosis and fixing specialist - analyzes errors, identifies root causes, provides fixes, and writes regression tests. Use for bug, debug, error, crash, traceback, exception, and regression work.