gemini-genai
Google python-genai SDK for Gemini 3 Flash, Gemini 3 Pro, and Gemini models. Use when building with Google's Gemini API, google-genai, implementing thinking/reasoning, structured outputs, function calling, image generation, or multimodal. Triggers on "gemini", "google ai", "genai".
code-review
Automated code review for pull requests using multiple specialized agents with confidence-based scoring to filter false positives
speech-recognition
iOS speech recognition implementation using @react-native-voice/voice. Use when debugging transcription issues, modifying session handling, or understanding the accumulated text tracking mechanism.
rag-wrapper
Patterns for wrapping any agent with RAG context from Qdrant. Use to add persistent memory to imported or external agents.
integrate-openai-agents
This skill should be used when integrating OpenAI Agents SDK with FastAPI, building message arrays from database history, running agents with MCP tools, parsing tool calls, executing them, and saving conversations to the database.
eld-sense-activation
PCE (Process-Context Engine) のアクティブコンテキスト構築スキル。タスクに最適化されたコンテキストをコンパイルし、プロセス駆動の投入物を生成する。 トリガー条件: - 新しいタスクを開始する時（「この機能を実装して」） - AIにコード生成を依頼する時 - 複雑な問題解決に着手する時 - 「コンテキストを整理して」 - 「必要な情報をまとめて」
selection-qa
Add selection-based Q&A functionality to ChatKit UI allowing users to ask about highlighted text with proper integration.
moai-ml-llm-fine-tuning
Enterprise LLM Fine-Tuning with LoRA, QLoRA, and PEFT techniques
plan-task-architectural
Use when the user asks for a plan or the task is complex/ambiguous. Enforces AGENTS.md workflow and encourages loading other relevant skills.
mova-skill-mova-ai-bootstrap-generate-basic-wrapper
Generates a static MOVA AI bootstrap pack for a target model/environment (no LLM calls). Input: env.mova_ai_bootstrap_generate_v1, output: ds.mova_ai_bootstrap_pack_v1.
create-claude-skill
Create new Claude skills following Anthropic best practices. Use when building specialized agent capabilities, packaging procedural knowledge, or extending Claude's domain expertise.
langgraph-patterns-expert
Use for LangGraph agent design and refactors. Prefer explicit state, small nodes, and clear transitions.
memory
AI agent long-term memory management skill (openmemory-py based). Store and retrieve conversation context, user preferences, and important information via semantic search. Note: Automatic context management is handled by the context-manager plugin. This skill is used when the agent **explicitly** manipulates memory. When to use: (1) When user requests memory save/retrieve → /memory add, /memory query (2) When agent determines additional context is needed → /memory query (3) When deleting unnecessary memories → /memory delete
model-first-reasoning
Two-phase reasoning paradigm that reduces hallucinations and constraint violations in complex planning tasks. Use when tasks involve multi-step planning, constraint satisfaction, resource allocatio...
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
a2a-agent
Comprehensive A2A (Agent-to-Agent) development toolkit for building Python agents using a2a-sdk and FastAPI. Use when creating new A2A agents, implementing agent handlers, adding streaming capabilities, testing agents, or deploying agents. Triggers include "a2a agent", "agent-to-agent", "a2a-sdk", "create agent", "agent handler", "streaming agent", or when working with FastAPI-based agent architectures.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
microsoft-agent-framework
Expert guidance for building AI agents using Microsoft Agent Framework. Use when creating single agents, multi-agent workflows, chat applications, or integrating tools with LLMs. Covers ChatAgent, tools (@ai_function), orchestration patterns (GroupChat, Sequential, Concurrent, Handoff), memory/state management, observability, and declarative YAML agents. Supports Python and .NET.
write-skill
Use when creating a new skill or updating an existing skills that extends Claude's capabilities.
parallel-agent-spawner
Spawn and coordinate parallel agents for faster completion. Use when running parallel tasks, spawning subagents, coordinating concurrent work, or optimizing throughput.
