multimodal-models
Use when "CLIP", "Whisper", "Stable Diffusion", "SDXL", "speech-to-text", "text-to-image", "image generation", "transcription", "zero-shot classification", "image-text similarity", "inpainting", "ControlNet"
Use when "CLIP", "Whisper", "Stable Diffusion", "SDXL", "speech-to-text", "text-to-image", "image generation", "transcription", "zero-shot classification", "image-text similarity", "inpainting", "ControlNet"
Creates new AI agent skills following the Agent Skills spec. Trigger: When user asks to create a new skill, add agent instructions, or document patterns for AI.
Create, configure, and document custom Claude Code subagents, including choosing scope, defining YAML frontmatter, selecting tools, model, permission mode, hooks, and usage examples.
Expert in building comprehensive AI systems, integrating LLMs, RAG architectures, and autonomous agents into production applications. Use when building AI-powered features, implementing LLM integrations, designing RAG pipelines, or deploying AI systems.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
Speech feedback to user via MCP audio servers. Use when providing status updates or asking questions.
Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
Configure agent specs, inheritance, skills, and tools in .parac/ workspace. Use when setting up or customizing agents.
AI Agent の実行ガイドライン。TDD サイクル、品質保証、コンテキスト管理、完了報告のルールを定義。すべての開発タスク実行時に使用。
Enterprise session state management, token budget optimization, runtime tracking, session handoff protocols, context continuity for Claude Sonnet 4.5 and Haiku 4.5 with context awareness features
Expert in creating visual grammar cheatsheets for Kabardian language with morphological breakdowns and corpus examples. Generates cheatsheets with ASCII-tree morpheme visualization (like verb_translation_cheatsheet.md). Activates when user requests grammar cheatsheet, mentions "создай шпаргалку", "cheatsheet for [category]", or wants visual breakdown of Kabardian grammar with real examples.
Comprehensive guide to effective prompt engineering patterns including few-shot, chain-of-thought, ReAct, and advanced prompting techniques
Analyze your gptme conversation history for insights like token usage, costs, model preferences, and usage patterns - inspired by Spotify Wrapped.
Generate a context handoff prompt before clearing the session. Use when the user wants to preserve conversation state before running /clear, or when ending a session and wanting to resume later. Creates a summary prompt capturing task state, progress, decisions, and next steps that can be pasted into a fresh session.
Determines minimal context and routes tasks to the correct prompts, agents and tools.
Use this skill when implementing quest automation in SND macros using the Questionable plugin. Covers command usage and integration with leveling workflows.
PocketFlow framework for building LLM applications with graph-based abstractions, design patterns, and agentic coding workflows
Expert prompt engineering for LLMs and AI agents. Use when users request help writing, reviewing, or improving prompts for chatbots, AI agents, system prompts, instruction sets, or any LLM-based application. Applies research-backed techniques to minimize hallucinations and maximize reliability.
Comprehensive guide to Claude Opus 4.5, Anthropic's most intelligent model with effort parameter for reasoning control. Covers model capabilities, benchmarks, effort levels (high/medium/low), hybrid reasoning, and model selection. Use when working with Opus 4.5, optimizing reasoning depth, choosing models, or understanding effort parameter trade-offs.
Routes to appropriate deep-RL skills based on problem type and algorithm family
Building AI agents and assistants with Convex. Use when implementing chat interfaces, AI assistants, tool-calling agents, RAG (retrieval-augmented generation), conversation threads, or integrating LLMs like OpenAI/Anthropic.
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 components (useChat, useCompletion), tool calling, structured data generation, provider management, streaming protocols, and advanced features like middleware and custom providers.