name: multi-agent-orchestration description: Use when three or more AI agents are available and a task needs coordinated execution, role assignment, independent verification, risk controls, or lower token/API cost. Activation is configurable: global, keyword-triggered, or manual.

Multi-Agent Orchestration

A capability-first coordination protocol with explicit ownership, evidence, stop conditions, and token-aware routing. It reduces error risk but cannot promise absolute infallibility.

Activation (when to use this skill)

Configure in config/agents.example.yaml under activation:.

Decide engagement before starting any work:

1. Read the activation block from config/agents.example.yaml.

2. If mode is global -> engage.

3. If mode is manual -> engage only when the user explicitly asked for multi-agent orchestration.

4. If mode is keyword -> run:

   node scripts/detect-trigger.mjs --text "" --config config/agents.example.yaml

   Exit code 0 (ENGAGED) means use this skill; exit code 1 (NOT_ENGAGED) means do not use it. Exclude keywords act as a veto even when a trigger keyword matched.

Fast Path

1. Discover each agent's tools, model, workspace, permissions, specialties, cost tier, and availability.
2. Map capabilities to roles; never infer from names alone.
3. Classify the task as routine, important, or critical using user configuration.
4. Create a compact task packet: objective, non-goals, ownership, risks, and acceptance tests.
5. Enforce one primary writer per file or resource.
6. For important work use specify -> implement -> verify -> accept.
7. For critical work add domain review and human approval for external or irreversible actions.
8. Stop on failed gates, ownership conflicts, missing evidence, or unapproved external actions.

Roles

Coordinator decomposes work, maintains state, resolves conflicts, and accepts evidence. Implementer edits assigned resources. Verifier independently tests behavior and regressions. Environment specialist diagnoses runtime, MCP, build, and toolchain problems. Domain reviewer checks UX, content, security, legal, or other domain criteria.

One agent may hold multiple roles for routine work only. Important work requires an independent verifier.

Token Policy

Load only the reference section needed. Use one coordinator summary instead of full transcripts. Send bounded structured packets. Parallelize independent read-only checks; serialize dependent work and writes. Use cheap models for discovery and mechanical checks; reserve strong models for ambiguity, architecture, adversarial review, and acceptance. Never compress requirements, code, paths, URLs, hashes, errors, permissions, or evidence.

See references/token-efficiency.md.

Completion Gate

Do not claim done, verified, or deployed without criterion-linked evidence. User-facing work should test actual runtime, target environments, core interactions, errors, keyboard/accessibility where relevant, resource loading, and fallback or reduced-motion behavior where relevant. A failed gate returns the task to its responsible stage.

See references/protocol.md, references/roles.md, and config/agents.example.yaml.

协同调度防翻车指南（八大坑与工程化解法）

多个 Agent 并行推进时的典型翻车点，组建团队前逐条对照。

硬性红线

• 禁止两成员同时写同一文件；禁止跳过看板直接开工/交付；
• 禁止把「我认为完成了」当完成——必须附运行证据；
• 禁止成员间私相授受任务（一切派发过总控）。

Multi-Agent Orchestration Skill

A portable, capability-first protocol for coordinating three or more AI agents with explicit ownership, independent verification, risk-based execution, and token-aware routing.

Features

• discovers capabilities instead of assuming agent names imply roles
• assigns coordinator, implementer, verifier, environment, and domain roles
• enforces one primary writer per file or resource
• adds a stronger pipeline for user-marked important or critical work
• stops on failed gates and requires evidence before completion claims
• reduces token and API cost with compact packets, bounded outputs, caching, parallel read-only checks, and model escalation

It does not provide an absolute guarantee; it makes failures visible, recoverable, and less likely.

Activation (when to use)

The skill engages in one of three modes, configured under activation: in config/agents.example.yaml:

• global - engages for every task
• keyword - engages only when the task text matches configured keywords (default; token-saving)
• manual - engages only when the user explicitly invokes it

For keyword mode, run the trigger detector before starting:

node scripts/detect-trigger.mjs --text "<task text>" --config config/agents.example.yaml

Exit code 0 means ENGAGED (use the skill); 1 means NOT_ENGAGED. Exclude keywords veto engagement even when a trigger matched.

Install

Option A: one-click installer (auto-detects common skill dirs).

Windows PowerShell:

powershell -ExecutionPolicy Bypass -File scripts/install.ps1

Linux/macOS shell:

./scripts/install.sh

Option B: clone and copy SKILL.md, references, and config into the skill directory supported by your host.

Validate your config locally:

node scripts/validate-config.mjs

Host adapter

Implement these five primitives: discover_agents, dispatch, lock, record, and approve. If a primitive is unavailable, use a documented manual fallback and record the limitation.

Usage

This is important. Three agents are available. Assign the best implementation agent, have another independently test it, and do not deploy.

Expected: capability inventory, role assignment, task packet, ownership lock, implementation evidence, independent verification, acceptance report, and awaiting_user_approval for deployment.

License

MIT.