Coil Selection & Thermal Design Agent

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后端代码生成 Skill，负责在 SoT 约束下生成 FastAPI 后端代码。

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前端代码生成 Skill，负责在 SoT 约束下生成 Next.js/React 前端代码。

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你是一个 **严格可控的 SoT 文档流水线执行器（Pipeline Runner）**：

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测试用例生成 Skill，负责根据 SoT 文档和业务代码生成 pytest 测试用例。

Master AI agent fundamentals - architectures, ReAct patterns, cognitive loops, and autonomous system design

Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.

Better proposals, faster closes. Use when creating AI agent pricing, automation proposals, ROI calculations, or sales materials. Generates professional pricing pages, case studies, and closing scripts for AI automation services.

Comprehensive L&D framework for upskilling DevOps/IaC/Automation teams to become AI Agent Engineers. Covers LLM literacy, RAG, agent frameworks, multi-agent systems, and LLMOps. Designed to help traditional automation teams compete with OpenAI and Anthropic.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.

Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)

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AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

Эксперт по data annotation. Используй для ML labeling, annotation workflows и quality control.

This skill should be used when reviewing AI-generated text, checking for AI writing patterns, detecting undisclosed AI content, or before finalizing any written content. Covers 12 categories of AI writing indicators from Wikipedia's comprehensive guide.

How to use AI APIs like OpenAI, ChatGPT, Elevenlabs, etc. When a user asks you to make an app that requires an AI API, use this skill to understand how to use the API or how to respond to the user.

ai-app

Expert-level AI system design, MLOps, architecture patterns, and AI infrastructure

Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the pattern into Claude Skills format.

Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.

Generate images via Nano Banana with 129 curated prompts. Mandatory validation interview refines style/mood/colors (use --skip to bypass). 3 modes: search, creative, wild. Styles: Ukiyo-e, Bento grid, cyberpunk, cinematic, vintage patent.

AI-powered development tools configuration and usage

Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.

AI-powered issue operations via gh-models. TRIGGERS - issue summarization, auto-labeling, issue insights.

The AI Board is a sophisticated reasoning system that dynamically selects and combines advanced LLM techniques to achieve maximum accuracy on complex questions. It uses multi-agent debate, adversarial

- {'principle': 'Brand is encoded in prompts, not just documents', 'why': 'AI tools need actionable instructions, not passive PDFs. Every brand\nguideline must translate to reusable prompts that AI ca

Embedding/vector caching for AI cost optimization

Use AI to merge individual page HTML files into a unified chapter document. Creates continuous document format for improved reading experience and semantic consistency.

Full-featured AI chatbot with Next.js 15, Auth.js, Drizzle ORM, and multi-model support.

Detect AI/LLM-generated text patterns in research writing. Use when: (1) Reviewing manuscript drafts before submission, (2) Pre-commit validation of documentation, (3) Quality assurance checks on research artifacts, (4) Ensuring natural academic writing style, (5) Tracking writing authenticity over time. Analyzes grammar perfection, sentence uniformity, paragraph structure, word frequency (AI-typical words like 'delve', 'leverage', 'robust'), punctuation patterns, and transition word overuse.

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Multi-turn conversational AI for intent extraction, clarification, and generation readiness detection. Guides users through articulating creative intent with structured parameter extraction.

Remove AI-generated code slop from branches. Use after AI-assisted coding

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AI-powered code generation for boilerplate, tests, data, and scaffolding

> **定位**: 独立的 AI 编程质量保障助手，重点关注代码质量提升和安全性

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