「multi-agent」の検索結果

Self-improvement loop for multi-agent workflows. Diagnose failures, improve tool descriptions, and learn from success/failure patterns.

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 assignment matrix, blocker escalation, and TDM coordination patterns. Use when assigning work to specialists, managing blockers, or coordinating multi-agent 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。

Initialize or improve AGENTS.md files that define how coding agents operate in a repo. Use when asked to set up or replace an agent init command (Codex, Claude), standardize multi-agent behavior, or audit an existing AGENTS.md for clarity, commands, boundaries, and repo-specific context. For Claude Code, also create CLAUDE.md as a symlink to AGENTS.md.

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 knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge management.

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 context manager specializing in information storage, retrieval, and synchronization across multi-agent systems. Masters state management, version control, and data lifecycle with focus on ensuring consistency, accessibility, and performance at scale.

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。

Manage agent fleet through CRUD operations and lifecycle patterns. Use when creating, commanding, monitoring, or deleting agents in multi-agent systems, or implementing proper resource 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。

Open protocol for AI agent interoperability enabling standardized communication between agents, applications, and humans across different frameworks

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Expert agent organizer specializing in multi-agent orchestration, team assembly, and workflow optimization. Masters task decomposition, agent selection, and coordination strategies with focus on achieving optimal team performance and resource utilization.

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。

Orchestrate a broad Incan review using specialized reviewer roles, parallel slice reports, and a canonical merged review report. Use when the user asks for delegated review, multi-agent review, or when a broad dirty worktree should be reviewed by specialized passes rather than one generic reviewer.

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 high-thoroughness end-to-end implementation loop using clean worker worktrees, per-slice planning, implementation, explicit review/fix iteration, orchestrator integration, and final commit/PR drafting. Use when the user explicitly wants a Ralph/Wiggum-style loop, autonomous multi-agent execution, a delegated feature/bugfix carried from confirmed scope through review-ready completion, or RFC-driven implementation that should be reviewed, bumped to In Progress, decomposed into phases, and executed through nested sub-loops. Supports Codex subagents by default and external CLI workers such as OpenCode when explicitly requested and available.

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。

Multi-agent adversarial code review. Spawns three reviewer subagents (Auditor, Adversary, Pragmatist) on a single model, runs a cross-examination round, then deterministically synthesizes a single ranked report. Use this for non-trivial PRs, security-sensitive changes, refactors that touch many files, or any change where one perspective has obvious blind spots. Trigger phrases include "adverse review", "adversarial review", "multi-perspective review", "review my changes from multiple angles", "panel review". NOT suitable for trivial diffs (typos, dependency bumps, formatting).

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。

Portable Codebase Argus agent playbook for evidence-first multi-agent review of GitHub pull requests, CI failures, GitHub Actions logs, GitHub App webhook review, /argus PR comment commands, autofix branch planning, OpenAI/Claude/Gemini/Codex provider tribunals, downstream merge/rebase work, and long-lived fork sync against an upstream 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。

Self-learning SEO content pipeline: dashboard, multi-agent queue, token budgets, research → write → audit → publish. StoryBrand/Cialdini/JTBD-style frameworks; config-driven. Use for content factory, batch articles, or scaled 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。

Track and manage tasks across multiple AI coding agents (Codex, Google Antigravity, Cursor, Gemini CLI, Claude Code) through the Mission Control web UI at http://localhost:6969. Use when you need a visual kanban for multi-agent work, dispatching tasks, monitoring agent activity, or syncing task state from a CLI 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。

Reference template for multi-agent orchestrated skills. Use as a pattern when creating complex skills that need parallel execution.

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 Google Agent Development Kit to define, test, evaluate, and deploy code-first Python agents with tools, sessions, HITL confirmation, and multi-agent orchestration.

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用于执行包含独立任务的实施计划，将任务分派给新的子代理，并在任务之间进行协调与审查。

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OctoClaw is the TypeScript-first policy, delegation, status, and operator layer for OpenClaw. Use it when a turn should be routed through reply/delegate policy, WorkContract-backed delegation, runtime status, IM delivery, or feedback-loop tooling.

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Build custom AI agents in Claude Code from a user's problem statement. This skill analyzes the user's use case, asks smart clarifying questions, researches the internet for similar agents (GitHub repos, blogs, Claude Code community patterns), and then architects and builds production-ready Claude Code agents — including subagents, skills, hooks, slash commands, MCP integrations, and CLAUDE.md configuration. Use this skill whenever the user wants to create an agent, build an automation workflow, set up a Claude Code subagent, design a multi-agent system, or says things like 'build me an agent for...', 'automate this with Claude Code', 'I want a subagent that...', 'help me create a workflow', 'set up an agent pipeline', or any variation of wanting Claude Code to do something specialized. Also trigger when the user mentions agent architecture, agent SDK, agentic workflows, or task delegation in Claude Code — even if they don't use the word 'agent' explicitly.

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Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.

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 task delegation patterns — spawn protocols, handoff metadata, drain gate, parallel limits, and model selection for multi-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。

Multi-agent swarm coordination patterns. Orchestrates parallel agent execution, manages agent communication, handles task distribution, and coordinates results aggregation.

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。

Autonomous iteration loop with dual-mode support. Standalone mode uses Stop hooks (RALPH_ACTIVE=1). Multi-agent mode uses router-managed iteration. Never traps the host/router session.

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。

Rates responses and plans against quality rubrics. Used for plan validation, response quality audits, and multi-agent consensus.

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。