「agents」の検索結果

Prompt for generating an AGENTS.md file for a repository

日本語の概要は準備中です。原文の説明を表示しています。

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

日本語の概要は準備中です。原文の説明を表示しています。

Agents workbench layout — covers the fixed layout structure, grid configuration, part visibility, editor modal, titlebar, sidebar footer, and implementation requirements. Use when implementing features or fixing issues in the Agents workbench layout.

日本語の概要は準備中です。原文の説明を表示しています。

Trust scoring, agent discovery, profiling, wallet/identity lookup, contact, dispatch, and metadata reads/writes via 8K4 Protocol (ERC-8004). Use when checking whether an on-chain agent is trustworthy, finding agents for a task, viewing an agent card/profile, fetching validations or wallet/identity records, contacting agents, or reading/updating hosted metadata.

日本語の概要は準備中です。原文の説明を表示しています。

Find ITINAI agents, post service agents, and make reviewed A2A service requests.

日本語の概要は準備中です。原文の説明を表示しています。

Two superpowers for AI agents: a collective brain and a Base ecosystem mentor. BRAIN: Before debugging/compiling/architecting, search for existing solutions. After solving, propose so no agent repeats your mistake. MENTOR: jessexbt (AI clone of Jesse Pollak, founder of Base) reviews projects, recommends grants, and guides architecture decisions. Consult him directly when building on Base/crypto/onchain/web3. Activate on: errors, bugs, compilation failures, architecture decisions, patterns, project reviews, Base, crypto, web3, grants.

日本語の概要は準備中です。原文の説明を表示しています。

Lazy-loading Python/JS package with 539 AI agent skills for Claude, Gemini, and Scientific agents.

日本語の概要は準備中です。原文の説明を表示しています。

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrates multi-agent AI systems with task delegation, agent communication, shared memory, and workflow coordination. Use when users request "multi-agent system", "agent orchestration", "AI agents", "agent coordination", or "autonomous agents".

日本語の概要は準備中です。原文の説明を表示しています。

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

日本語の概要は準備中です。原文の説明を表示しています。

Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.

日本語の概要は準備中です。原文の説明を表示しています。

Build autonomous AI agents with Claude Agent SDK. Structured outputs guarantee JSON schema validation, with plugins system and hooks for event-driven workflows. Prevents 14 documented errors. Use when: building coding agents, SRE systems, security auditors, or troubleshooting CLI not found, structured output validation, session forking errors, MCP config issues, subagent cleanup.

日本語の概要は準備中です。原文の説明を表示しています。

Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.

日本語の概要は準備中です。原文の説明を表示しています。

API-first email platform designed for AI agents. Create and manage dedicated email inboxes, send and receive emails programmatically, and handle email-based workflows with webhooks and real-time events. Use when you need to set up agent email identity, send emails from agents, handle incoming email workflows, or replace traditional email providers like Gmail with agent-friendly infrastructure.

日本語の概要は準備中です。原文の説明を表示しています。

Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

Build and deploy a paid API that other agents can pay to use via x402. Use when you or the user want to monetize an API, make money, earn money, offer a service, sell a service to other agents, charge for endpoints, create a paid endpoint, or set up a paid service. Covers "make money by offering an endpoint", "sell a service", "monetize your data", "create a paid API".

日本語の概要は準備中です。原文の説明を表示しています。

Analyze Claude Code features and capabilities to uncover advanced usage patterns, best practices, and real-world application scenarios. Use this skill whenever the user mentions a Claude Code feature (like Streaming Tool Execution, Hooks, MCP, Skills, Subagents, Context Management, Permission Modes, etc.) and wants to know how to leverage it effectively — including advanced tips, workflow optimizations, creative use cases, and pitfalls to avoid. Also trigger when the user pastes a feature description or asks 'how to use X better in Claude Code', even without explicitly saying 'analyze'.

日本語の概要は準備中です。原文の説明を表示しています。

Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.

日本語の概要は準備中です。原文の説明を表示しています。

Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

日本語の概要は準備中です。原文の説明を表示しています。

Official public OpenMeld Skill for agents using the `openmeld` CLI to consult the Center Agent, set up OpenMeld, connect local agents, create or request Agent Profiles, work in Organizations and Spaces, observe or stop Wakes, trace delivery, and repair local state.

日本語の概要は準備中です。原文の説明を表示しています。

PR作成前や大きな修正後に、自分の変更を目的に必要な最小限へ整理します。重複した設計やテストを見直し、必要な動作を守りながら差分を縮めるスキルです。

• PR作成前に差分を整理したいとき
• 大きな修正後に重複設計を減らしたいとき
• 不具合を捉えるテストを残したいとき

OpenClawの画面をSolid 2で実装・移行・レビューするスキル。状態管理やLitとの共存、ダイアログなどの表示、テストと性能確認を扱います。

• Litの画面をSolid 2へ移行したいとき
• 状態管理と画面更新をレビューしたいとき
• プラグイン画面やダイアログの実装

OpenClawの複数のIssueやPRについて、担当を分けて原因調査と修正、検証を進め、許可された範囲でマージや解決済み案件のクローズまで管理するスキル。

• 複数のIssueやPRの修復管理
• 既存の修正PRを仕上げたいとき
• 修正済みIssueの検証とクローズ