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brigade_run

Launch an asynchronous brigade of parallel subagents to decompose, implement, verify, review, and summarize a software-engineering task, returning an ID for status polling.

Instructions

出动多子代理军团执行一个软件工程任务(架构师拆解→影子目录隔离实现→产物+exec 机器验收→审查闸门→summary.md)。子代理通过本机 opencode CLI 运行,默认使用 opencode 当前配置的模型(可能产生费用)(可用 model 参数或 LEGION_MODEL 环境变量覆盖)。异步:立即返回 mcpId,用 brigade_status 轮询。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdYes工作目录绝对路径,改动会合并回这里(必填)
goalYes要完成的目标,一句话(必填)
hintsNo给架构师的补充约束
modelNo子代理使用的模型 id,格式 provider/model(如 opencode/beam-free,以你本机可用模型为准);不填则用 opencode 当前默认模型或 LEGION_MODEL 环境变量。注意:默认模型可能是付费模型,会产生费用,请自行确认
noTestNo关闭测试环节
noReviewNo关闭审查环节
timeoutSecNo单任务超时秒数,默认 900
maxParallelNo并发子代理数,默认 3,上限 8

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does well: it discloses that this is asynchronous (returns mcpId immediately), that sub-agents use the local opencode CLI, that costs may be incurred, and that the default model is overridable via model param or LEGION_MODEL. It omits permission/auth requirements and how the cwd is affected, but the cost and async warnings are genuinely valuable behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense but front-loaded paragraph that opens with the core action and pipeline, then layers cost and async notes. Nothing is padded, though the parenthetical cost caveat appears twice, slightly reducing efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter, no-output-schema, no-annotation tool, the description supplies the pipeline, async contract, and cost model an agent needs to invoke it responsibly. Return-value details beyond mcpId are minimal, but polling via brigade_status covers the follow-up, leaving only minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 8 parameters including model defaults, timeouts, and concurrency limits. The description largely restates the model/cost behavior already present in the schema and adds no further parameter semantics, making the baseline 3 correct.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — launching a multi-sub-agent brigade for a software engineering task — and even outlines the internal pipeline (architect → shadow-dir implementation → verification → review gate → summary). It distinguishes itself from siblings by naming brigade_status as the mechanism to poll results.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains the async execution model and explicitly routes the agent to brigade_status for polling, which is the key usage decision. It does not, however, contrast with brigade_template or state when NOT to run a full brigade, so the sibling guidance is partial rather than exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.