generate-note
Generate new text or code content from scratch using natural language prompt via LLM. Use to collect thoughts or generate a coherent statement on a topic
Generate new text or code content from scratch using natural language prompt via LLM. Use to collect thoughts or generate a coherent statement on a topic
Generate or edit images with Gemini Pro. Use when user says "generate an image", "create a picture", "make me a logo", "edit this image", "remove the background", "change the style", "combine these images", "add text to image", "style transfer", "make a sticker", "product mockup", or any image creation/manipulation request. Handles t2i (text-to-image), i2i (image-to-image editing), and multi-reference composition.
Search the ComfyUI custom nodes registry for plugins and extensions. Use when the user wants to find specific custom nodes, ComfyUI extensions, or plugins by name, functionality, or description.
LiteLLM-RS Streaming Architecture. Covers UnifiedSSEParser, SSETransformer trait, VecDeque buffering, provider-specific transformers, and real-time event handling.
Creates production-grade, reusable skills that extend Claude's capabilities. This skill should be used when users want to create a new skill, improve an existing skill, or build domain-specific intelligence. Gathers context from codebase, conversation, and authentic sources before creating adaptable skills.
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
Create and update ai-context.md files that document modules for AI assistants. Use when adding documentation for packages, apps, or external references that should be discoverable via /modules commands.
Take a ScienceWorld action in the active session. Returns observation, reward, done. No session_id needed - uses active session from executive_node.
Perform security audits on Agent Skills from a given path. Use when the user asks to audit, review, check security, or verify a skill for security issues.
LiteLLM-RS A2A Protocol Architecture. Covers Agent-to-Agent communication, JSON-RPC 2.0 messaging, multi-provider orchestration, agent registry, and task state management.
Search past Claude Code conversations. Use when user says "search conversations", "find that chat", "what did we discuss", "where did we talk about", "look up past session", "find conversation about X", "search history", "what did I ask about", "remember when we", "that discussion about". Also triggers on past-tense questions referencing prior work or possessives without context.
LiteLLM-RS Configuration Architecture. Covers YAML loading, environment variable override, validation patterns, type-safe config models, and hot reloading.
LiteLLM-RS Provider 开发与架构指南。用于添加新 provider、迁移错误处理、维护 66+ provider 的一致性。包含架构对比分析和最佳实践。
Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
LiteLLM-RS Routing Architecture. Covers 7 routing strategies, lock-free design with DashMap, health-aware selection, fallback chains, and load balancing.
Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.
Configure and compose AI provider layers using @effect/ai packages. Covers Anthropic, OpenAI, OpenRouter, Google, and Amazon Bedrock providers with config management, model abstraction, and runtime overrides for language model integration.
LiteLLM-RS Error Handling Architecture. Covers two-tier error hierarchy, ProviderError factory methods, HTTP status mapping, retry logic, and error context preservation.
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
LiteLLM-RS Provider Architecture Guide. Covers 66+ provider integration, trait object design, unified error handling, connection pooling, and LLMProvider trait implementation patterns.
A simple example skill that demonstrates Claude Code skill structure