agent-team-orchestration
- Repo stars 1,996
- Author updated Live
- Author repo openclaw-master-skills
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @LeoYeAI · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- macOS · Linux · Windows
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-team-orchestration
description: Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review…
category: ai
runtime: no special runtime
---
# agent-team-orchestration output preview
## PART A: Task fit
- Use case: 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..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Quick Start: Minimal 2-Agent Team / 1. Define Roles / 2. Spawn a Task” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “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.”.
- **02** When the source has headings, the agent prioritizes “Quick Start: Minimal 2-Agent Team / 1. Define Roles / 2. Spawn a Task” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/shared`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Quick Start: Minimal 2-Agent Team / 1. Define Roles / 2. Spawn a Task”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agent-team-orchestration
description: Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review…
category: ai
source: LeoYeAI/openclaw-master-skills
---
# agent-team-orchestration
## When to use
- Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when:…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Quick Start: Minimal 2-Agent Team / 1. Define Roles / 2. Spawn a Task” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agent-team-orchestration" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Quick Start: Minimal 2-Agent Team / 1. Define Roles / 2. Spawn a Task
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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 (handles judgment) |
| Builder | Produce artifacts — code, docs, configs | Can use cost-effective models for mechanical work |
| Reviewer | Verify quality, push back on gaps | High-reasoning model (catches what builders miss) |
| Ops | Cron jobs, standups, health checks, dispatching | Cheapest model that's reliable |
→ 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:
- What was done — summary of changes/output
- Where artifacts are — exact file paths
- How to verify — test commands or acceptance criteria
- Known issues — anything incomplete or risky
- 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_spawndirectly. 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.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review