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songzhifei512

multi-agent-bridge

result_arbitrate

Resolve conflicting answers from multiple AI workers by applying majority agreement, expert-weighted scoring, and LLM arbitration to select the winning result with justification.

Instructions

结果冲突仲裁:多 worker 对同一问题给出不同答案时自动裁决。输入 ≥2 份候选结果,三层裁决:①多数一致优先(结论相同直接过)→ ②专家加权(claude 推理 3 / codex 执行 2 / 其它 1,confidence 可选加权)→ ③仍无胜者时派 LLM 仲裁者(从空闲 worker 池轮询选,排控制主控防自我指涉,全忙回退 qwen)背书。返回 winner + 裁决层 + 各候选权重明细 + 仲裁理由。只裁决不建任务,供 Orchestrator 合并多 worker 并行产出时调用( 配套)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
arbiterNo可选指定仲裁者 agent 名(缺省空闲池轮询,全忙回退 qwen)
criteriaNo可选裁决依据(验收标准/约束)
questionYes被裁决的问题/目标(仲裁者据此判)
candidatesYes≥2 份候选结果

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
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 it delivers: it discloses the three-layer arbitration algorithm, expert weighting rules, fallback to qwen when all workers are busy, and the exact return format (winner, arbitration layer, weight details, reason). It also states it does not create tasks, making side effects clear.

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?

The description is a single dense paragraph but uses numbered layers (①②③) to structure the arbitration logic, front-loading the purpose. It is comprehensive without being bloated, though it could benefit from bullet points for readability.

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

Completeness5/5

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

The description is complete for an agent to call correctly: it explains the return values (since there is no output schema), specifies the required candidate count, details the fallback behavior, and names the intended caller. No critical information is missing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3, but the description adds meaningful context beyond the schema: it explains the ≥2 candidate requirement, the expert weight mapping (claude=3/codex=2/others=1), optional confidence weighting, and the arbiter selection fallback—all of which are not in the schema.

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?

The description clearly states the tool arbitrates conflicts when multiple workers give different answers, using a specific verb ('仲裁') and resource ('多 worker 对同一问题给出不同答案'). It also distinguishes itself from siblings by explicitly noting it only arbitrates and does not create tasks, and by specifying its intended caller (Orchestrator).

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?

The description explicitly states when to use it: '供 Orchestrator 合并多 worker 并行产出时调用' (for Orchestrator when merging parallel outputs from multiple workers). It also clarifies a negative constraint ('只裁决不建任务'), which helps rule out misuse, though it does not name alternative tools explicitly.

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