<skill>

<skill>

<skill>

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。

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.

ai-app

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

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

Design co-learning experiences using the Three Roles Framework (AI as Teacher/Student/Co-Worker). Use when teaching AI-driven development workflows, spec-first collaboration, or balancing AI assistance with foundational learning. NOT for curriculum without AI integration.

You are a specialized cross-validation assistant that uses Google's Gemini 2.5 Pro API to provide independent, multi-perspective code validation alongside Claude's analysis.

Fetches AI news from smol.ai RSS and generates structured markdown with intelligent summarization and categorization. Optionally creates beautiful HTML webpages with Apple-style themes and shareable card images. Use when user asks about AI news, daily tech updates, or wants news organized by date or category.

Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create visualizations, or build predictive models with reproducible, code-based workflows.

Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.

AI Elements component library for AI-native applications. Use when building chatbots, AI workflows, or integrating with Vercel AI SDK's useChat hook.

Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations. Use when building LLM features, chatbots, AI-powered applications, or need guidance on AI/ML engineering patterns.

Build production-ready LLM applications, advanced RAG systems, and

Practical guide for building production ML systems based on Chip Huyen's AI Engineering book. Use when users ask about model evaluation, deployment strategies, monitoring, data pipelines, feature engineering, cost optimization, or MLOps. Covers metrics, A/B testing, serving patterns, drift detection, and production best practices.

In traditional software, inputs and outputs are defined. In AI, inputs and outputs are fuzzy. Evals (evaluations) are the "unit tests" for AI products. They allow you to move from "vibes-based" develo

Help users create and run AI evaluations. Use when someone is building evals for LLM products, measuring model quality, creating test cases, designing rubrics, or trying to systematically measure AI output quality.

Create an AI Evals Pack (eval PRD, test set, rubric, judge plan, results + iteration loop). Use for LLM evaluation, benchmarks, rubrics, error analysis/open coding, and ship/no-ship quality gates for AI features.

Integrate AI tools and APIs into business workflows and applications

ai-llm-engineering

Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting.

A production-ready pattern for integrating AI models (specifically Google Gemini) with automatic fallback, retry logic, structured output via Zod schemas, and comprehensive error handling. Use when integrating AI/LLM APIs, need automatic fallback when models are overloaded, want type-safe structured responses, or building features requiring reliable AI generation.

Design AI-powered immersive NPC systems for escape room games using proven actor techniques from Korean immersive escape rooms (Danpyeonsun, Ledasquare). Implements adaptive dialogue, emotional simulation, player profiling, and trust dynamics using Gemini/GPT-4. Creates character profiles with lying probabilities, improvisational responses, and cost-optimized streaming. Use for murder mystery NPCs, suspect interrogation, or dynamic character interactions.

Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini APIs.

Effective communication strategies for AI-assisted development. Learn context-first prompting, phased interactions, iterative refinement, and validation techniques to get better results from Claude and other AI coding assistants.

Production best practices for building AI agents with Vercel AI SDK v5. Covers security, performance, error handling, testing, deployment patterns, and real-world implementation guidelines.

Manages AI SDK model configurations - updates packages, identifies missing models, adds new models with research, and updates documentation

Vercel AI SDK tool patterns for dx-toolkit - input schemas for smart queries, API key handling, raw response returns

ai-sdk-ui

GitHub repository skill for Mallikarjun-Roddannavar/ai-testcase-generator-mcp

Generate high-quality training datasets from documents, text corpora, and structured content. Use when creating AI training data from dictionaries, documents, or when generating examples for machine learning models. Optimized for low-resource languages and domain-specific knowledge extraction.

Analyze transcript files using OpenAI API (gpt-5-mini) to extract insights, summaries, key topics, quotes, and action items. This skill should be used when users have transcript files (from WhisperKit, YouTube, podcasts, meetings, etc.) and want AI-powered analysis, summaries, or custom insights extracted from the content. Supports both default comprehensive analysis and custom prompts for specific information extraction.

MANDATORY verification system that prevents Claude Code instances from making false claims or fabricating evidence. Enforces cryptographic verification, real testing evidence, and automatic claim validation before any success statements can be made.

Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.

Skill to assist with how a GitHub repository is configured with GitHub integrations, including instructions for agents in markdown (AGENTS and CLAUDE), github actions for invoking agents, and specific

Create AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly.

生成、维护、修剪AICTXT文档，保持在CRAFT大小限制内。当AICTXT创建和更新时使用。

AIEOS (AI Entity Object Specification) is a standardization framework designed to solve the "identity crisis" currently facing AI agents. Combined with Soul Documents, together they form a comprehensi

Cross-agent communication system for AI workflows. Check messages at session start, send notifications to other agents, and track multi-agent handoffs with correlation IDs.

Setup and use Docker AI (Gordon) for intelligent container operations

Debug and implement Airtable synchronization logic including duplicate prevention, cache management, change detection, and RLS considerations; use when debugging sync failures, stale cache issues, or implementing new Airtable sync features

Use the aissist CLI tool for personal goal tracking, todo management, daily history logging, context-specific notes, guided reflections, and AI-powered semantic recall. Activate when users mention goals, tasks, todos, progress tracking, journaling, work history, personal assistant, meal planning, fitness tracking, or want to search their past activities and reflections.

aiworkflow-requirements

Diagnose and fix Kubernetes deployment failures, especially ImagePullBackOff, CrashLoopBackOff, and architecture mismatches. Battle-tested from 4-hour AKS debugging session with 10+ failure modes resolved.

Alchemy IaC patterns for deploying TanStack Start apps to Cloudflare Workers with D1 databases. Use when setting up new TanStack Start projects, configuring Alchemy deployments, working with D1/Drizzle migrations, local development with Cloudflare bindings, or deploying to custom domains.

A skill for managing database migrations with Alembic. Use this for tasks involving Alembic initialization, configuration, creating new migration scripts (both autogenerated and manual), defining upgrade and downgrade logic, handling data migrations, testing migrations, performing rollbacks, and following production deployment best practices for database changes.

1. **Alert-based triggers:**