Orchestrates a dual-AI engineering loop where Claude Code plans and implements, while Codex validates and reviews, with continuous feedback for optimal code quality
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge,...
This skill should be used when users need to work with the Vercel AI SDK for building AI-powered applications. It provides comprehensive guidance on core APIs (generateText, streamText), UI...
This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context...
Documentation-first development methodology. The goal is AI-ready documentation - when docs are clear enough, code generation becomes automatic. Triggers on "Build", "Create", "Implement",...
Run Claude Code (Anthropic) from this host via the `claude` CLI (Agent SDK) in headless mode (`-p`) for codebase analysis, refactors, test fixing, and structured output. Use when the user asks to...
Run Claude Code (Anthropic) from this host via the `claude` CLI (Agent SDK) in headless mode (`-p`) for codebase analysis, refactors, test fixing, and structured output. Use when the user asks to...
Transform Claude Code into an autonomous software engineer using Context Engineering. Use when starting a new project, planning features, building code, verifying work, or documenting decisions....
Master the AI tools that automate repetitive work and connect your tools. From simple Zapier integrations to complex AI-powered workflows, reclaim hours every week. Use when "automation, workflow,...
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
为 Claude Code 会话提供的正式评测框架，实现了评测驱动开发（Eval-Driven Development，EDD）原则
Set up Claude Code to route requests through Vercel AI Gateway for monitoring and observability
Real-time monitoring dashboard - system metrics, process monitoring, and resource tracking
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with...
Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing multi-language...
Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to...
Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse...
Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models...
This sop guides the implementation of code tasks using test-driven development principles, following a structured Explore, Plan, Code, Commit workflow. It balances automation with user...
Generates new Ralph hat collection presets through guided conversation. Asks clarifying questions, validates against schema constraints, and outputs production-ready YAML files.