「agent」の検索結果

Drives a multi-turn conversation with a LiveKit agent running locally to see what it does. Use when the user says "test my agent", "try my agent", "does this work", "why did it call that tool", "it says the wrong thing when I ask X", "test this change", or whenever you have edited an agent and need to check how it behaves. Wraps `lk agent debugger`: start the agent in text mode, send turns, read the tool calls, handoffs, errors and logs behind each reply, and restart after an edit. It runs without audio or a LiveKit room at one LLM call per turn, so it is the preferred way for a coding agent to live-test during development, and the default when the user says "test" without naming unit tests or simulations.

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Help a technical founder build whatever they want on Claude Managed Agents — an internal worker, a piece of their product, a customer-facing agent. Find out what they want to build, scope a v0, launch it in their account, grade it, iterate, and (if it should run on a clock) put it on a scheduled deployment, with everything bigger laid out as v1/v2. Use when a founder says "launch my agent", "/launch-your-agent", "build me a managed agent", or wants to build something on CMA. Keywords: managed agents, CMA, founder, launch, scheduled deployment, outcome rubric.

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特工宇宙/仲泰（Agent Universe，国内首个聚焦AI智能体AI Agent的垂直科技自媒体）的内容创作思维——Agent垂直深耕+实操导向+产品体验验证+社区分发闭环+AI Agent翻译器。 触发词：「特工宇宙视角」「像特工宇宙那样写」「仲泰」「AI Agent圣经」「观猹」「AI智能体教程」「智能体评测」。 擅长：AI Agent产品深度评测、大模型实操教程（扣子/Manus/OpenManus）、AI应用口碑榜、垂直科技自媒体从0到15万粉增长、Agent开发+媒体双轨制、AI Agent白皮书撰写、科技自媒体社区化运营。

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Write the code for a CopilotKit Channels agent with the Channels SDK (@copilotkit/channels) — a platform-agnostic engine that puts one AG-UI agent into Slack, Microsoft Teams, Discord, Telegram, and WhatsApp with native interactive UI. It's the engine behind OpenTag, the open-source alternative to Claude in Slack. Use this whenever the user wants to create, scaffold, or extend a Channels agent; wire an agent into Slack/Teams/Discord; add a tool, slash command, button, select, modal, or human-in-the-loop confirmation to a chat agent; or asks about createChannel, defineChannelTool, defineChannelComponent, thread.runAgent, awaitChoice, or the channels-ui JSX components. Trigger even when the user says "Slack bot", "Discord bot", or "chat agent" without naming the SDK, as long as the context is CopilotKit / Channels. The Channels API is new and easy to get wrong from memory — always ground code in this skill.

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Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.

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AGENTS.md / CLAUDE.md 最佳实践顾问。用于用户询问 agents markdown、AGENTS.md、CLAUDE.md、Claude Code memory、AI coding agent 指令文件的格式、结构、最佳实践；也用于审查、诊断、重写、优化或从零创建 AGENTS.md、CLAUDE.md、CLAUDE.local.md、.claude/rules 等 agent 指令文件。不适用于通用 README 写作，除非目标是给 AI coding agent 提供项目上下文。

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Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming. Prevents 11 documented errors. Use when: building agents with tools, voice agents with WebRTC, multi-agent workflows, or troubleshooting MaxTurnsExceededError, tool call failures, reasoning defaults, JSON output leaks.

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Use when you need to generate a checklist document with embedded agents inventory, following the embedded template exactly and producing INVENTORY-AGENTS-JAVA.md in the project root. This should trigger for requests such as Create embedded agents inventory checklist; Generate INVENTORY-AGENTS-JAVA.md; Use @002-agents-inventory; Inventory embedded Java agent definitions; List generated agent roles for Java development. Part of Plinth Toolkit

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Universal discipline for any LM-driven loop — agent retries, plan-act-observe, multi-agent handoffs, optimiser passes, test-fix cycles. Encodes the one rule every framework documents quietly and every team relearns expensively: the LM in the loop is NEVER a reliable terminator. Termination must be provided by an explicit counter + exit predicate + stagnation signal + escalation path that live OUTSIDE the LM's control. This is a tool- level, framework-agnostic skill. It maps onto LangGraph (recursion_limit + state counter + interrupt), CrewAI (max_iter + max_rpm + human_input), Claude / OpenAI SDKs (max_iterations + tool_use_budget), DSPy (declared evaluation budget), Aider (REPL + explicit retry cap), and AutoGen (max_consecutive_auto_reply). Search keywords: infinite loop, recursion limit, recursion_limit, GraphRecursionError, max iterations, max_iter, agent stuck, agent won't stop, runaway agent, ReAct loop not terminating, agent repeating itself.

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原始人スタイル subagent への委譲判断ガイド。`genshijin-investigator` (コード位置特定)、 `genshijin-builder` (1-2ファイル編集)、`genshijin-reviewer` (diff レビュー) を inline作業 or vanilla `Explore` の代わりにスポーンするタイミングを示す。subagent 出力は原始人圧縮 → 主コンテキストに戻る tool-result が約60%縮小 → 長セッション持続。 Trigger: 「subagent 委譲」「genshijin-crew 使用」「investigator/builder/reviewer 起動」「コンテキスト節約」「圧縮 agent 出力」。

Audit and recommend improvements for a repository's agent-readable context, including AGENTS.md, CLAUDE.md, WARP.md, CONTRIBUTING.md, .agents/skills, and specs/ PRODUCT.md and TECH.md contracts. Use when asked to review, score, assess, or standardize repo instructions, agent onboarding, spec workflows, or cross-repo agent-context conventions. Use agentsmd-scaffold instead when the user wants to generate or apply root/scoped AGENTS.md files.

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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.

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Agent 基建：把任意 skill 或 skill 集合目录桥接到 Claude Code（~/.claude/skills）、Codex（~/.codex/skills）、通用 Agents（~/.agents/skills，豆包 Mac App / Trae Solo / Codex 可读取）和 Grok（~/.grok/skills）。支持 dbskill 仓库内 skill，也支持外部 skill 绝对路径。Claude / Codex / 通用 Agents 使用软链，Grok 生成带 user_invocable: true 的薄 bridge。支持按 skill 名称、相对路径、绝对路径、skills 目录批量桥接，也支持拆桥和查看桥接状态。 触发方式：/dbs-bridge、/bridge、「桥接这个 skill」「桥接整个 skills 目录」「把这个 skill 接到 Claude Code、Codex、豆包和 Grok」「让多个 Agent 都能调用这个 skill」「取消桥接」「查看桥接状态」 Bridge any skill folder or directory of skill folders to Claude Code, Codex, generic Agents (~/.agents/skills), and Grok using symlinks plus Grok bridge files. Supports dbskill skills and external skill directories. Use when the user wants one or many skills callable from multiple agents, or wants to unlink/check bridge status. Trigger: /dbs-bridge, /bridge, "bridge this skill", "bridge this skills directory", "make this skill available to Claude Code, Codex, Doubao, and Grok", "unlink this skill", "check bridge status"

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Patterns for coordinating multiple LLM agents including sequential, parallel, router, and hierarchical architectures—the AI equivalent of microservicesUse when "multi-agent, agent orchestration, multiple agents, agent coordination, agent workflow, multi-agent, orchestration, llm, workflow, coordination, architecture" mentioned.

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Agent Performance Optimization Workflow workflow skill. Use this skill when the user needs Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Multi-Agent Optimization Toolkit workflow skill. Use this skill when the user needs Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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 Optimization Toolkit workflow skill. Use this skill when the user needs Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Maintaining AGENTS.md workflow skill. Use this skill when the user needs This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Manages Neo4j Aura Agents via the v2beta1 REST API — create, list, get, update, delete, and invoke Aura agents backed by an AuraDB instance. Use when configuring Aura Agent tools (CypherTemplate, SimilaritySearch, Text2Cypher), setting system prompts, deploying agents to REST or MCP endpoints, invoking agents with natural language queries, or generating evaluation datasets (max 50 questions) for the Aura Agent evaluation feature. Covers OAuth2 auth, organization/project scoping, tool parameter schemas, and InvokeAgentResponse format. Does NOT cover AuraDB instance provisioning — use neo4j-aura-provisioning-skill. Does NOT cover vector index creation — use neo4j-vector-index-skill.

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AI Agent Workflow & Skill Architecture Guide — turn expert work into measurable, reusable agent systems. Covers workflow discovery, skill decomposition, harness design, evaluation, human escalation, observability, cost control, and multi-agent orchestration. Includes a measured marketing-delivery case: 15 people × 3–4 weeks reduced to one strategist + AI in 5 days. By Gingiris.

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Provides best practices for AI agent orchestration including MCP servers, A2A protocol, multi-agent coordination, and swarm architectures. Use when designing agent systems, configuring MCP servers, setting up agent teams, or when user mentions 'MCP', 'A2A', 'agent orchestration', 'multi-agent', 'swarm', 'agent team', 'LangGraph', 'CrewAI', 'AutoGen'.

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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.

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Build production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production deployment.

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AI agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.

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。