implement-sonnet
Implement code using sonnet model with full main context access
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Implement code using sonnet model with full main context access
Use this skill for [purpose]. Triggers when user mentions [keywords]. Provides guidelines, templates, and standards for [domain].
Creates, analyzes, updates, and improves Claude Code hooks including configuration, scripts, and security validation. Use when user asks how hooks work, explaining hook concepts, understanding hook types and event lifecycle, describing hook configuration, creating new hooks, analyzing existing hooks for improvements, validating hook security, debugging hook activation, updating hook configurations, or when user mentions "hook", "PreToolUse", "PostToolUse", "SessionStart", or other hook event types. Handles both command hooks and prompt-based hooks across all 9 event types.
Create narrative lore entries that transform technical work into mythological stories. Use when generating agent memory, documenting changes as narrative, or building persistent knowledge through storytelling.
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools, resources, and prompts. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks safely, reliably, and with predictable outputs.. Use when Use this skill when the task matches its description and triggers..
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
Create interactive learning games for business English practice. Supports multiple game types (quiz, simulation, drag-drop) across various business scenarios (emails, meetings, presentations, negotiations). Generate HTML/React-based games tailored to user's industry, job role, and proficiency level. Use when users request business English learning games, practice materials, interactive training content, or educational exercises for professional English communication.
AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.
Browser automation and inspection for AI agents via WebSocket
Create a template file for human reviewers to write free-form feedback before AI code review.
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools, resources, and prompts. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks safely, reliably, and with predictable outputs.. Use when Use this skill when the task matches its description and triggers..
Generate SAT methodology-compliant training courseware for Prometheus PCGS 2.0. Use for: (1) Creating lesson plans with proper SAT structure, (2) Generating presentations from course content, (3) Building timetables with duration calculations, (4) Producing trainee handbooks, (5) Exporting course specification sheets, (6) Validating Bloom's Taxonomy alignment. Triggers: lesson plan, presentation, timetable, handbook, course specification, SAT, Bloom's Taxonomy, CLO, learning outcome, training material, courseware, assessment, performance criteria.
Build AI agents with OpenAI Agents SDK, tool registration, conversation history, and stateless execution. Use when creating AI agents, registering tools, or handling conversations.
The ultimate unified development skill combining 25+ programming languages, 9+ BaaS providers, 6+ development functions, and 15+ security capabilities with AI orchestration, Context7 integration, enterprise compliance, and end-to-end project automation
LLM integration patterns for Claude, GPT, Gemini, and Ollama. Activate for AI API integration, prompt engineering, token management, and multi-model orchestration.
Query AI model specifications, pricing, and capabilities from models.dev database. Use when users ask about AI model parameters (context window, token limits, cost per token), model comparisons, provider information, or need to look up specific model IDs for AI SDK integration. Triggers on queries like "What's the context window for GPT-4o?", "Compare Claude vs GPT", "How much does Gemini Pro cost?", "List OpenAI models", or "What models support tool calling?".
End-to-end system for creating supervised fine-tuning datasets from books and training style-transfer models. Covers text extraction, intelligent segmentation, synthetic instruction generation, Tinker-compatible output, LoRA training, and validation.