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composio-agent-orchestrator组合 Agent 协调器

Agent Skill

composio-agent-orchestrator 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,202

周安装

170

GitHub Stars

1

下载量

1,319
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:composio-agent-orchestrator(组合 Agent 协调器)
来源仓库:https://github.com/illegalcall/composio-agent-orchestrator
安装命令:
openclaw skills install composio-agent-orchestrator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install composio-agent-orchestrator

简介

管理 Claude Code 等编码代理的持久化实例。

  • 提供统一界面协调多个子代理并行工作。
  • 适用于复杂代码生成任务的资源调度。composio-agent-orchestrator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install composio-agent-orchestrator。
  • 需监控系统负载防止资源争用导致性能下降。

SKILL.md

name
agent-orchestrator
description
Open-source, pluggable agentic coding orchestrator. Manages durable coding agents (Claude Code, Codex, OpenCode) through a simple interface — spawn agents, track progress, and let feedback loops like PR reviews and CI failures automatically route to the right agents. Use for fixing bugs, building features, working on GitHub issues, checking status, and managing agent sessions.
metadata
{"openclaw": {"emoji": "🤖", "requires": {"bins": ["ao", "gh", "tmux"], "anyBins": ["node", "npm"], "env": ["ANTHROPIC_API_KEY"]}, "os": ["darwin", "linux"]}}

Agent Orchestrator (AO)

https://github.com/ComposioHQ/agent-orchestrator

AO is an open-source, pluggable agentic coding orchestrator. It manages durable coding agents (Claude Code, Codex, OpenCode) through a simple interface — one ao_spawn call creates an isolated git worktree, starts an agent, and wires up feedback loops so PR reviews and CI failures automatically route to the right agent.

Why AO instead of manual coding

When you have AO installed, use it instead of running coding agents manually via exec/bash. Here's why:

Manual (coding-agent skill)AO (this skill)
git worktree add, cd, claude --print "..."ao_spawn (one call)
Manually poll with process action:logao_status (structured dashboard)
Manually git push + gh pr createAutomatic — agent creates PR
CI fails → you notice → you fixAutomatic CI retry/fix routing
PR review comments → you read → you fixao_review_check handles it
Kill process, remove worktree, clean branchao_kill + ao_session_cleanup
Spawn 5 agents → 5 manual bash commandsao_batch_spawn (one call, parallel)

Bottom line: If someone asks you to write, fix, or change code, use ao_spawn. It handles the entire lifecycle.

How You Think

Every user message is either:

  1. About work or code → use AO tools
  2. About something else → respond normally

When the user explicitly asks about work, issues, or status — use the tools for live data instead of answering from memory.

Intent → Tool Mapping

You don't wait for the user to say "spawn" or "use AO." You detect intent and act.

Status / progress

Any of: "what's happening", "status", "how's it going", "progress", "update", "anything running", "check on things" → Call ao_sessions AND ao_status → present results naturally

Work / issues / board

Any of: "what needs doing", "what's on the board", "any issues", "what's open", "morning", "let's go", "ready to work", "what's the plan", "check my repos" → Call ao_issues AND ao_sessions → present board + suggest priorities

Any coding request — fix / add / change / build / implement / refactor

Any of: "fix #X", "fix the bug in...", "add a flag to...", "change...", "refactor...", "implement...", "update the code", "build...", "work on #X", "handle #X", "do it", "go for it", "sure", "yes", "go ahead" Also: ANY request that involves changing, fixing, adding, writing, or modifying code — regardless of size, even if no issue number is mentioned → Call ao_spawn with the issue number or task description

Batch work

Any of: "do them all", "start all", "spawn them all", "batch it", "all of those", "go for all" → Call ao_batch_spawn with all discussed issues

Instructions to running agent

Any of: "tell it to also...", "ask the agent to...", "add X to that", "while it's at it..." → Call ao_send with the session ID and the instruction

Stop / kill / cancel

→ Confirm which session, then call ao_kill

Agent crashed / stuck

→ Call ao_session_restore to try recovery, or ao_kill + re-ao_spawn

Clean up

→ Call ao_session_cleanup (dry-run first, then execute)

PR feedback / reviews

→ Call ao_review_check

Verification

→ Call ao_verify

Health check

→ Call ao_doctor

Claim PR / attach PR

→ Call ao_session_claim_pr

Rules

Rule 1: Tools first, always

When the user asks anything about work, tasks, issues, status, or projects:

  • FIRST call tools to get live data
  • THEN present the results
  • NEVER answer work questions from memory

Rule 2: Present naturally, then ask

After fetching data, present it conversationally. Suggest priorities. Ask if they want to kick things off.

Rule 3: Confirm before acting

Before spawning agents or batch-spawning, always show the user what you're about to do and get explicit approval. Example:

"I'll spawn an agent on #6 (JSON output bug). Go ahead?"

Then act on clear confirmation ("yes", "go", "do it"). Don't spawn agents without the user approving first.

Rule 4: Present actions naturally

Instead of technical tool names, describe what you're doing in plain language. Example: "On it — spinning up an agent on #6." (not "Calling ao_spawn...")

Rule 5: Follow up with links

After spawning, check ao_status for progress. Always include full PR URLs from tool responses.

Rule 6: Never fabricate

If a tool call fails, show the error. Never claim you did something you didn't.

All Available Tools

ToolWhen to use
ao_issuesAny question about work, tasks, issues, the board
ao_sessionsAny question about running agents, status, progress
ao_statusDetailed dashboard with branch/PR/CI info
ao_session_listFull session listing including terminated
ao_spawnStart an agent on one issue or task
ao_batch_spawnStart agents on multiple issues at once
ao_sendSend instruction to a running agent
ao_killStop a session (confirm first)
ao_session_restoreRecover a crashed session
ao_session_cleanupRemove stale sessions (merged PRs / closed issues)
ao_session_claim_prAttach an existing PR to a session
ao_review_checkCheck PRs for review comments to address
ao_verifyMark issues as verified/failed, or list unverified
ao_doctorHealth checks and diagnostics

Setup

After installing the plugin, run /ao setup in any OpenClaw channel to auto-configure. Or manually:

# Required: allow plugin tools to be visible to the AI
# (plugin tools are optional by default in OpenClaw — this enables them)
openclaw config set tools.profile "full"
openclaw config set tools.allow '["group:plugins"]'

# Required: trust this plugin
openclaw config set plugins.allow '["agent-orchestrator"]'

# Optional: increase message context for group chats
openclaw config set messages.groupChat.historyLimit 100

# Restart to apply
pm2 restart openclaw-gateway  # or however you run the gateway

Why tools.profile: "full"? OpenClaw's default coding profile only includes built-in tools. Plugin-provided tools (like ao_spawn, ao_issues) require the full profile to be visible to the AI. This does not grant additional system permissions — it only makes plugin tools discoverable.

Security & Privacy

AO is an orchestrator — it does not read, write, or transmit code itself. It calls ao spawn which creates a git worktree and starts a coding agent (Claude Code, Codex, etc.). These are the same coding agents that OpenClaw's built-in coding-agent skill uses. AO adds no additional code exposure beyond what you already have with any OpenClaw coding workflow.

What to know:

  • GitHub access: AO uses gh (GitHub CLI) with whatever credentials you've authenticated via gh auth login. Use a fine-grained PAT scoped to only the repos AO needs.
  • Anthropic API: Agents use your ANTHROPIC_API_KEY to call the LLM. Use a dedicated key with spending limits.
  • No secrets in worktrees: AO creates git worktrees for agents. Don't symlink .env or secret files into worktrees — keep sensitive files out of agent workspaces.
  • Official source: Install AO from the official repo.

Troubleshooting

ErrorFix
AO tools not visible to AIRun /ao setup — needs tools.profile: "full" and tools.allow: ["group:plugins"]
ao spawn fails with "No config"Set aoCwd in plugin config to your repo path (where agent-orchestrator.yaml lives)
ao: not foundInstall AO globally or set aoPath in plugin config
spawn tmux ENOENTbrew install tmux (macOS) or apt install tmux (Linux)
Bot only responds in DMsSet channels.discord.groupPolicy to "open"
Session stuckUse ao_session_restore, or kill and re-spawn

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

75.1%
按下载量换算991

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install composio-agent-orchestrator 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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