Agent助手
- 作者仓库星标 7,233
- 作者更新于 实时读取
- 作者仓库 agent-orchestrator
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @ComposioHQ · 未声明 license
- Token 消耗评级
- 中等消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 需要 · Anthropic
- 兼容的系统
- macOS · Linux · Windows
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 读取环境变量
- 网络行为
- 允许外网请求
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-orchestrator
description: Open-source, pluggable agentic coding orchestrator. Manages durable coding agents (Claude Code…
category: AI 智能
runtime: 无特殊运行时
---
# agent-orchestrator 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Why AO instead of manual coding / How You Think / Intent → Tool Mapping”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Why AO instead of manual coding / How You Think / Intent → Tool Mapping”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、读取环境变量、会按任务需要访问外部网络、需要准备 Anthropic API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令、读取环境变量;会按任务需要访问外部网络;需要准备 Anthropic API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文出现了 `/ao` 这类斜杠命令;如果你的 Agent 支持命令触发,优先用命令开场,再补充目标和边界。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令、读取环境变量。
先用一个小任务确认它会围绕“Why AO instead of manual coding / How You Think / Intent → Tool Mapping”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: agent-orchestrator
description: Open-source, pluggable agentic coding orchestrator. Manages durable coding agents (Claude Code…
category: AI 智能
source: ComposioHQ/agent-orchestrator
---
# agent-orchestrator
## 什么时候使用
- 用于审阅代码、文档或方案并给出可执行反馈 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;使用前要准…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Why AO instead of manual coding / How You Think / Intent → Tool Mapping」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令、读取环境变量;会按任务需要访问外部网络;需要准备 Anthropic API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "agent-orchestrator" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Why AO instead of manual coding / How You Think / Intent → Tool Mapping
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件、执行终端命令、读取环境变量 | 会按任务需要访问外部网络
安全层 -> 需要准备 Anthropic API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Agent Orchestrator (AO)
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:log |
ao_status (structured dashboard) |
Manually git push + gh pr create |
Automatic — agent creates PR |
| CI fails → you notice → you fix | Automatic CI retry/fix routing |
| PR review comments → you read → you fix | ao_review_check handles it |
| Kill process, remove worktree, clean branch | ao_kill + ao_session_cleanup |
| Spawn 5 agents → 5 manual bash commands | ao_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:
- About work or code → use AO tools
- 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 if one exists, or with just the task description if there is no issue
Issue number is optional. Both of these are valid:
- With issue: user says "fix #42" → spawn with
issue: "42" - Without issue: user says "add a weekly report script" → spawn with no issue, just confirm the 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. Examples:
- With issue: "I'll spawn an agent on #6 (JSON output bug). Go ahead?"
- Without issue: "I'll spawn an agent on this task: 'Add weekly report script'. 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. Examples:
- With issue: "On it — spinning up an agent on #6." (not "Calling ao_spawn...")
- Without issue: "On it — spinning up an agent on that task." (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
| Tool | When to use |
|---|---|
ao_issues |
Any question about work, tasks, issues, the board |
ao_sessions |
Any question about running agents, status, progress |
ao_status |
Detailed dashboard with branch/PR/CI info |
ao_session_list |
Full session listing including terminated |
ao_spawn |
Start an agent on one issue or task |
ao_batch_spawn |
Start agents on multiple issues at once |
ao_send |
Send instruction to a running agent |
ao_kill |
Stop a session (confirm first) |
ao_session_restore |
Recover a crashed session |
ao_session_cleanup |
Remove stale sessions (merged PRs / closed issues) |
ao_session_claim_pr |
Attach an existing PR to a session |
ao_review_check |
Check PRs for review comments to address |
ao_verify |
Mark issues as verified/failed, or list unverified |
ao_doctor |
Health 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 viagh auth login. Use a fine-grained PAT scoped to only the repos AO needs. - Anthropic API: Agents use your
ANTHROPIC_API_KEYto call the LLM. Use a dedicated key with spending limits. - No secrets in worktrees: AO creates git worktrees for agents. Don't symlink
.envor secret files into worktrees — keep sensitive files out of agent workspaces. - Official source: Install AO from the official repo.
Troubleshooting
| Error | Fix |
|---|---|
| AO tools not visible to AI | Run /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 found |
Install AO globally or set aoPath in plugin config |
spawn tmux ENOENT (macOS / Linux) |
brew install tmux (macOS) or apt install tmux (Linux) |
spawn tmux ENOENT (Windows) |
Your config has runtime: tmux set explicitly. Switch to runtime: process (or remove the override — process is the Windows default; ConPTY is used natively, no tmux required) |
| Bot only responds in DMs | Set channels.discord.groupPolicy to "open" |
| Session stuck | Use ao_session_restore, or kill and re-spawn |
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核