AI assistant for creating clear, actionable task descriptions for GitHub Copilot agents
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →AI assistant for creating clear, actionable task descriptions for GitHub Copilot agents
Interactive prompt engineering coach that elevates vague prompts through Socratic dialogue, multiple transformation styles, and guided learning. Use when improving prompts, learning agentic engineering, or wanting coached guidance rather than automated transformation. NEVER auto-executes - always displays and asks first.
Use when building AI agent systems. Covers agent loops, tool calling, planning patterns, memory systems, multi-agent coordination, and safety guardrails. Apply when creating autonomous AI workflows, coding assistants, or task automation systems.
Write clear, plain-spoken code comments and documentation that lives alongside the code. Use when writing or reviewing code that needs inline documentation like file headers, function docs, architectural decisions, or explanatory comments. Works well for both human readers and AI coding assistants who see one file at a time.
Features in LivestockAI must now be designed for **dual consumption**: Humans (UI) and Agents (MCP/API).
Architecture guidelines for Jarvy CLI - codebase structure, tool implementation patterns, registry system, platform-specific code organization, and module conventions.
Code quality guidelines for Jarvy CLI - Rust formatting, Clippy linting, error handling patterns, documentation standards, and Conventional Commits.
Performance optimization guidelines for Rust CLI tools. Covers efficient command execution, parallel processing, lazy initialization, allocation minimization, config parsing, and build optimizations for cross-platform CLI applications.
Testing guidelines for Jarvy CLI - unit testing patterns, integration tests with assert_cmd, test environment variables, platform-specific testing, and CI coverage strategies.
Track and measure agentic coding KPIs for ZTE progression. Use when measuring workflow effectiveness, tracking Size/Attempts/Streak/Presence metrics, or assessing readiness for autonomous operation.
Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.
Design and operate multi-agent orchestration patterns (ReAct loops, evaluator-optimizer, orchestrator-workers, tool routing) for LLM systems. Use when building or debugging agent workflows, tool-use loops, or multi-step task delegation; triggers: agentic, multi-agent, orchestration, ReAct, evaluator-optimizer, tool-use, handoff.
Design, review, and improve agent workflows & agent using SSOT, SRP, Fail Fast principles. Supports Prompt Chaining, Parallelization, Orchestrator-Workers patterns.
Design and implement agentic AI workflows and patterns. Covers ReAct, planning agents, tool use, memory systems, and multi-agent orchestration. Use when building autonomous AI agents, implementing complex task automation, or designing intelligent workflow systems.
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Generate a project-specific AGENTS.md from a user goal, then confirm before overwriting.
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
Branch skill for building and improving agents. Use when creating new agents, adapting marketplace agents, validating agent structure, writing system prompts, or improving existing agents. Triggers: 'create agent', 'improve agent', 'validate agent', 'fix agent', 'agent frontmatter', 'system prompt', 'adapt agent', 'customize agent', 'agent examples', 'agent tools'.
AIコーディングエージェント向けの指示書「AGENTS.md」を作成するスキル。プロジェクトにAIエージェントが作業するための文脈と指示を集約するファイルを作成したい場合に使用します。「AGENTS.mdを作成」「AIエージェント用の指示書を作る」「エージェント向けREADMEを作成」などのリクエストでトリガーします。OpenAI Codex、Claude Code、GitHub Copilot、Cursorなど、複数のAIエージェントで共通利用できるオープンな標準フォーマットです。
Generate hierarchical AGENTS.md structures optimized for AI coding agents with minimal token usage.
Keeps repo-local agent instructions consistent by proposing updates to AGENTS.md when a user corrects the coding agent or asks to change AGENTS.md, CLAUDE.md, .claude/CLAUDE.md, or GEMINI.md.
Create or update root and nested AGENTS.md files that document scoped conventions, monorepo module maps, cross-domain workflows, and (optionally) per-module feature maps (feature -> paths, entrypoints, tests, docs). Use when the user asks for AGENTS.md, nested agent instructions, or a module/feature map.
Dynamic agent composition and management system. USE WHEN user says create custom agents, spin up custom agents, specialized agents, OR asks for agent personalities, available traits, agent voices. Handles custom agent creation, personality assignment, voice mapping, and parallel agent orchestration.
AgentsKB - Knowledge Base API for AI Agents with 32K+ technical Q&As
Instructions for debugging agentstack-server during development
Display the API key for the currently authenticated user. Requires authentication. Use for managing authentication credentials
Display information about the currently authenticated user. Requires authentication. Use for managing authentication credentials
Get details about a specific agent. Requires authentication. Use for Agentuity cloud platform operations
Get a specific API key by id. Requires authentication. Use for Agentuity cloud platform operations
Show details about a specific database. Requires authentication. Use for Agentuity cloud platform operations
Get query logs for a specific database. Requires authentication. Use for Agentuity cloud platform operations
View logs for a specific deployment. Requires authentication. Use for Agentuity cloud platform operations
Remove a specific deployment. Requires authentication. Use for Agentuity cloud platform operations
Rollback the latest to the previous deployment. Requires authentication. Use for Agentuity cloud platform operations
Show details about a specific deployment. Requires authentication. Use for Agentuity cloud platform operations
Undeploy the latest deployment. Requires authentication. Use for Agentuity cloud platform operations
Get details about a specific eval. Requires authentication. Use for Agentuity cloud platform operations
Get details about a specific eval run. Requires authentication. Use for Agentuity cloud platform operations
List deployments running on a specific organization managed machine. Requires authentication. Use for Agentuity cloud platform operations
Get details about a specific organization managed machine. Requires authentication. Use for Agentuity cloud platform operations
Get information about a specific execution. Requires authentication. Use for Agentuity cloud platform operations
Get information about a sandbox. Requires authentication. Use for Agentuity cloud platform operations
Get details about a specific session. Requires authentication. Use for Agentuity cloud platform operations
Get logs for a specific session. Requires authentication. Use for Agentuity cloud platform operations
Show details about a specific storage bucket. Requires authentication. Use for Agentuity cloud platform operations
Get detailed information about a specific stream. Requires authentication. Use for Agentuity cloud platform operations
Get details about a specific thread. Requires authentication. Use for Agentuity cloud platform operations
Get a specific vector entry by key. Requires authentication. Use for Agentuity cloud platform operations
Build and run the development server