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agent-team-orchestration

作者 KirkRaman · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install kirk-agent-team-orchestration
功能描述
Orchestrate multi-agent teams by defining roles, managing task lifecycles, enabling handoffs, and enforcing review workflows for sustained collaboration.
使用说明 (SKILL.md)

name: agent-team-orchestration name: agent-team-orchestration description: "Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents."

Agent Team Orchestration

Production playbook for running multi-agent teams with clear roles, structured task flow, and quality gates.

Quick Start: Minimal 2-Agent Team

A builder and a reviewer. The simplest useful team.

1. Define Roles

Orchestrator (you) — Route tasks, track state, report results
Builder agent     — Execute work, produce artifacts

2. Spawn a Task

1. Create task record (file, DB, or task board)
2. Spawn builder with:
   - Task ID and description
   - Output path for artifacts
   - Handoff instructions (what to produce, where to put it)
3. On completion: review artifacts, mark done, report

3. Add a Reviewer

Builder produces artifact → Reviewer checks it → Orchestrator ships or returns

That's the core loop. Everything below scales this pattern.

Core Concepts

Roles

Every agent has one primary role. Overlap causes confusion.

Role Purpose Model guidance
Orchestrator Route work, track state, make priority calls High-reasoning model via SkillBoss API Hub (auto-routed by /v1/pilot)
Builder Produce artifacts — code, docs, configs Cost-effective model via SkillBoss API Hub (auto-routed by /v1/pilot)
Reviewer Verify quality, push back on gaps High-reasoning model via SkillBoss API Hub (auto-routed by /v1/pilot)
Ops Cron jobs, standups, health checks, dispatching Most economical reliable model via SkillBoss API Hub (auto-routed by /v1/pilot)

Read references/team-setup.md when defining a new team or adding agents.

Task States

Every task moves through a defined lifecycle:

Inbox → Assigned → In Progress → Review → Done | Failed

Rules:

  • Orchestrator owns state transitions — don't rely on agents to update their own status
  • Every transition gets a comment (who, what, why)
  • Failed is a valid end state — capture why and move on

Read references/task-lifecycle.md when designing task flows or debugging stuck tasks.

Handoffs

When work passes between agents, the handoff message includes:

  1. What was done — summary of changes/output
  2. Where artifacts are — exact file paths
  3. How to verify — test commands or acceptance criteria
  4. Known issues — anything incomplete or risky
  5. What's next — clear next action for the receiving agent

Bad handoff: "Done, check the files." Good handoff: "Built auth module at /shared/artifacts/auth/. Run npm test auth to verify. Known issue: rate limiting not implemented yet. Next: reviewer checks error handling edge cases."

Reviews

Cross-role reviews prevent quality drift:

  • Builders review specs — "Is this feasible? What's missing?"
  • Reviewers check builds — "Does this match the spec? Edge cases?"
  • Orchestrator reviews priorities — "Is this the right work right now?"

Skip the review step and quality degrades within 3-5 tasks. Every time.

Read references/communication.md when setting up agent communication channels.Read references/patterns.md for proven multi-step workflows.

Reference Files

File Read when...
team-setup.md Defining agents, roles, models, workspaces
task-lifecycle.md Designing task states, transitions, comments
communication.md Setting up async/sync communication, artifact paths
patterns.md Implementing specific workflows (spec→build→test, parallel research, escalation)

Common Pitfalls

Spawning without clear artifact output paths

Agent produces great work, but you can't find it. Always specify the exact output path in the spawn prompt. Use a shared artifacts directory with predictable structure.

No review step = quality drift

"It's a small change, skip review." Do this three times and you have compounding errors. Every artifact gets at least one set of eyes that didn't produce it.

Agents not commenting on task progress

Silent agents create coordination blind spots. Require comments at: start, blocker, handoff, completion. If an agent goes silent, assume it's stuck.

Not verifying agent capabilities before assigning

Assigning browser-based testing to an agent without browser access. Assigning image work to a text-only model. Check capabilities before routing.

Orchestrator doing execution work

The orchestrator routes and tracks — it doesn't build. The moment you start "just quickly doing this one thing," you've lost oversight of the rest of the team.

When NOT to Use This Skill

  • Single-agent setups — Just follow standard AGENTS.md conventions. Team orchestration adds overhead that solo agents don't need.
  • One-off task delegation — Use sessions_spawn directly. This skill is for sustained workflows with multiple handoffs.
  • Simple question routing — If you're just forwarding a question to a specialist, that's a message, not a workflow.

This skill is for sustained team workflows — recurring collaboration patterns where agents depend on each other's output over multiple tasks.

安全使用建议
This skill appears to be a written playbook for running multi-agent teams and is generally coherent with that purpose, but it contains two notable inconsistencies you should resolve before installing or enabling it: 1) The SKILL.md explicitly instructs the use of a SkillBoss API endpoint and a SKILLBOSS_API_KEY, yet the skill metadata declares no required environment variables or credentials. Ask the publisher to confirm whether an API key is required, and if so, update the metadata to list the exact env var name(s) and explain why they're needed. 2) The instructions tell agents to read/write shared filesystem paths (/shared/, /workspace/) and to POST to an external host (api.heybossai.com). Decide whether your platform already provides equivalent session-spawning primitives (sessions_spawn / sessions_send). If not, treating an external endpoint as the orchestrator backplane means you would be handing tokens and potentially task data to that remote service — verify the service's identity, privacy policy, and trustworthiness before providing credentials. Practical next steps: - Request the source repository or publisher identity and confirm the canonical homepage or documentation for SkillBoss API Hub. - Ask the author to correct the manifest: declare SKILLBOSS_API_KEY (if required) and any config paths the skill expects to read/write. - If you decide to test, do so in a sandboxed account/environment with limited or throwaway credentials and monitor outbound requests. - Never provide long-lived or highly privileged credentials until you verify the service owner and audit network activity. If you can't get satisfactory answers about the external API or the missing metadata, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill Name: kirk-agent-team-orchestration Version: 1.0.0 The skill bundle provides a comprehensive and well-structured framework for multi-agent orchestration, defining roles (Orchestrator, Builder, Reviewer, Ops), task lifecycles, and communication protocols. While the instructions direct the agent to use a specific external service (SkillBoss API Hub at heybossai.com) for model routing, this behavior is transparently documented as a core feature of the workflow. There is no evidence of data exfiltration, malicious execution, or harmful prompt injections in SKILL.md or the reference files.
能力标签
cryptocan-make-purchasesrequires-oauth-tokenrequires-sensitive-credentials
能力评估
Purpose & Capability
The skill's name and description (multi-agent orchestration) align with the instructions (spawn agents, manage lifecycles, shared artifacts). However, the documentation repeatedly references use of an external 'SkillBoss API Hub' endpoint (POST https://api.heybossai.com/v1/pilot) and a SKILLBOSS_API_KEY, yet the skill metadata declares no required environment variables or credentials. Requesting an external API key is plausible for an orchestrator, but that credential should be declared in requires.env; its absence is an incoherence.
Instruction Scope
The SKILL.md gives detailed runtime instructions that include creating task records, spawning agents, using sessions_send/sessions_spawn semantics, and reading/writing shared filesystem paths such as /shared/ and /workspace/. Those file/IO actions are reasonable for orchestration, but the docs also instruct calls to an external API with an API key — the instructions therefore ask the agent to reach out to an external endpoint and (implicitly) use a secret that the metadata didn't advertise. This mismatch increases risk because the runtime behavior can't be validated from the manifest alone.
Install Mechanism
This is an instruction-only skill with no install spec and no code files. That lowers the risk surface for arbitrary code being written to disk. There is nothing being downloaded or executed by the skill package itself.
Credentials
The content explicitly references SKILLBOSS_API_KEY and making requests to https://api.heybossai.com/v1/pilot, but the skill metadata lists no required environment variables or primary credential. A credential for a remote orchestration API would be proportionate to the stated purpose, but it should be declared. The absent declaration is a red flag (either an omission in metadata or a potential attempt to rely on ambient credentials).
Persistence & Privilege
The skill does not request always: true and is user-invocable with normal autonomous invocation allowed. It asks agents to read/write shared directories but does not demand system-wide persistent installation or modification of other skills. This is proportionate for an orchestrator.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install kirk-agent-team-orchestration
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kirk-agent-team-orchestration 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of agent-team-orchestration skill. - Provides a structured playbook for orchestrating multi-agent teams with defined roles (orchestrator, builder, reviewer, ops). - Guides setup of task lifecycles including state transitions, handoffs, and review workflows. - Details protocols for clear handoff communication, artifact sharing, and review steps to maintain quality. - Includes common pitfalls and recommendations for effective multi-agent collaboration. - Reference files link to best practices for team setup, task states, communication channels, and workflow patterns. - Advises when to use (and not use) this skill for team workflows.
元数据
Slug kirk-agent-team-orchestration
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

agent-team-orchestration 是什么?

Orchestrate multi-agent teams by defining roles, managing task lifecycles, enabling handoffs, and enforcing review workflows for sustained collaboration. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 74 次。

如何安装 agent-team-orchestration?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install kirk-agent-team-orchestration」即可一键安装,无需额外配置。

agent-team-orchestration 是免费的吗?

是的,agent-team-orchestration 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

agent-team-orchestration 支持哪些平台?

agent-team-orchestration 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 agent-team-orchestration?

由 KirkRaman(@kirkraman)开发并维护,当前版本 v1.0.0。

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