「agents」の検索結果

Build original LangGraph agents for Warden Protocol and prepare them for publishing in Warden Studio. Use this skill when users want to: (1) Create new Warden agents (not community examples), (2) Build LangGraph-based crypto/Web3 agents, (3) Deploy agents via LangSmith Deployments or custom infra, (4) Participate in the Warden Agent Builder Incentive Programme (open to OpenClaw agents), or (5) Integrate with Warden Studio for Agent Hub publishing.

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。

Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.

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。

Use when modifying agentic contextual building blocks like skills (SKILL.md), slash commands, agents, hooks, plugins, marketplaces, and instruction files (CLAUDE.md, AGENTS.md, GEMINI.md, QWEN.md, Cursor, Copilot, Cline, or Kiro rules), tool configuration such as an OpenCode `opencode.json`, Muse Code hooks (`.muse/hooks.json`), a Grok Build `.grok/` project layer or a Google Antigravity customization root (`.agents/`, `.agent/`, `_agents/`, `_agent/` — hooks, MCP config, rules, registries and plugins), and committed project memory (`.agents/memory/`). Run skillsaw on the files you touched, apply autofixes, resolve remaining violations with `skillsaw explain` guidance, and re-lint until clean before considering the work complete.

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。

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'.

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。

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。

Built by DynG AI for PlatformPilot.ai-style multi-agent systems. Use when designing or reasoning about message-passing agent coordination in ANY language: actor-style mailboxes, select, point-to-point routing, pub/sub, fan-in joins/quorums, ownership handoff, budgets, dead letters, and traces. Trigger words include PlatformPilot, DynG AI, actor model agents, message-passing agents, CSP agents, coordinate agents, multi-agent orchestration, agent runtime, fan-out workers, pub/sub agents, agent barrier, or join.

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。

Deploy, run, list, or tear down the agents in this repo's .managed-agents/ folder on Anthropic Managed Agents. Use when the user says "deploy my agents", "ship this agent to the cloud", "run the deployed agent", or asks about managed-agent deployment.

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。

Run a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.

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。

Use this skill to maintain an agent log in .agents/log, a decision journal shared by the developer and agents. Trigger when the user explicitly asks to use agent-log or record/update an agent log entry; when planning, implementing, or finalizing a significant feature in a repo with an existing .agents/log; or before non-trivial changes or questions in areas covered by existing entries. Never initialize .agents/log unless the user explicitly asks for an agent log.

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 AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.

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。

Codex workflow tips from Boris Cherny (creator of Codex) and the Codex team. Use when: setting up Codex, optimizing workflows, running parallel sessions, configuring AGENTS.md, using skills/commands, subagents, hooks, MCP integrations, or learning best practices. Covers: git worktrees, plan mode, verification, permissions, Slack MCP, BigQuery, prompting tips, plugins, custom agents, sandboxing, keybindings, status lines, output styles, customization, /simplify for code quality, /batch for parallel code migrations, /loop for scheduled tasks, code review agents, /btw for mid-task questions, /effort max reasoning, remote control sessions, voice mode, setup scripts, session naming, /color, PostCompact hook, auto mode, /schedule cloud jobs, iMessage plugin, auto-memory, and auto-dream, mobile app, session teleporting, Cowork Dispatch, Chrome extension, Desktop app, /branch forking, --bare SDK startup, --add-dir multi-repo, --agent custom agents, /voice input.

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。

Splits one big Claude task or automation into a set of focused AI Matrx agents that work on the person's own AI Matrx tables, then builds and test-runs each one. Use when the person says "split my task into agents", "turn my automation into AI Matrx agents", "make agents for my work", or after their data has moved into AI Matrx.

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。

Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent systems, implementing A2A protocol, exposing agents as services, consuming remote agents, configuring agent cards, or when user mentions A2A, agent-to-agent, multi-agent collaboration, remote agents, or agent orchestration.

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。

This skill should be used when the user asks about "parallel agents", "background tasks", "run_in_background", "non-blocking agents", "check agent progress", "TaskOutput", "retrieve agent results", or discusses running multiple agents concurrently. Covers patterns for launching agents in background, monitoring progress, and retrieving results.

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。

技術文書やエージェント向け指示ファイルを作成・レビューするスキル。READMEや貢献手順も調べ、説明の分かりやすさ、運用上の整合性、多言語版の差分を確認します。

• 技術文書を作成・更新したいとき
• READMEや文書の変更レビュー
• エージェント指示と貢献手順の整備

互いに依存しない不具合やテスト失敗を別々のエージェントに割り当て、並行して調査・修正するスキル。担当範囲を明確にし、結果の確認と変更の統合まで案内します。

• 原因の異なるテスト失敗を調べたいとき
• 別々の機能の不具合を修正したいとき
• 複数エージェントの担当を整理したいとき

長期的な目標に向けて複数のサブエージェントの作業を調整し、利用者との対話を続けながら、次の仕事にも役立つ作業環境や規約の改善を進めるスキル。

• 長期目標に向けて担当を調整したいとき
• 裏で作業を進めながら対話を続けたいとき
• 共通の規約や作業環境を改善したいとき

AIエージェントがスキルやルールを実際に守るか、指示の強さが異なる３段階のシナリオで検証し、遵守率とツール呼び出しの時系列をレポートにまとめます。

• 追加したルールの遵守確認
• 念押しなしで手順が守られるか確認
• ツール実行順序と抜けの確認

AIエージェントが実装の多くを担う開発チーム向けに、計画、責任分担、レビュー基準、テスト要件を整理し、生成コードを扱う開発プロセスを設計するスキル。

• AI生成コードを扱う開発ルールの整備
• コードレビュー基準と承認条件の設定
• エージェントが作業しやすい設計の検討

複数の Claude Code エージェントに開発作業を割り振り、個別の作業環境で並行実行しながら、依存関係・進捗・変更内容やエラーの報告を管理するスキル。

• 開発計画を依存関係付きで分割したいとき
• 個別の作業環境で並行開発したいとき
• 複数の開発タスクの進捗確認

2つのエージェントが別々に加えた変更のGit競合を、双方の差分と意図から中立的に解決。競合箇所ごとの判断理由を記録し、ビルドやテストで統合結果を確認します。

• 2つのエージェントのブランチ競合を解消
• 並行したworktreeの変更を統合
• 競合する設計判断の理由を確認したいとき

Spawn nested sub-agents (agents that spawn sub-agents, up to depth=5) via Claude Code's native Task tool — for context-managed deep delegation

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。

Codex-only team orchestration: run a named team of cooperating Codex workers with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of agents/threads/sessions, or to work on something as a team in parallel. FIRST inspects the active tool surface (checking tool_search for deferred tools) and tells the user the route: native MultiAgentV2 agents (flat spawn_agent with task_name) when available, Codex App threads as the fallback, or a plain-subagent split when neither set exists. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team.

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。

Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.

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。