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coeus_critical_debate

Run an adversarial Red vs Blue debate on plans, designs, or code to uncover critical flaws and propose mitigations.

Instructions

Execute a Red Team vs Blue Team adversarial debate on a plan, design, or code snippet to identify critical flaws and mitigations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoDepthdeep
contentYesContent
contextNoContext
red_modelNoRed model
blue_modelNoBlue model
synthesis_modelNoSynthesis model
timeout_per_stepNoTimeout per step
adversarial_pointsNoAdversarial points

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.8/5.0
Behavior3/5

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

The description discloses the core behavior: an adversarial debate and a result aimed at flaws and mitigations. With no annotations, though, it does not indicate return format, model-invocation behavior, or cost/latency implications, leaving some behavioral expectations implicit.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no filler. It efficiently communicates action, input scope, and purpose.

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

Completeness2/5

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

Given eight parameters, no output schema, and no annotations, one sentence is insufficient. It omits return structure, depth semantics, timeout behavior, and how the model-related parameters work together, leaving meaningful gaps for an agent deciding whether and how to invoke the tool.

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 coverage is 100%, so the baseline applies. The description adds marginal value by hinting that 'content' is the plan, design, or code snippet being debated, but it does not clarify ambiguous parameters like 'context', 'adversarial_points', or how the red/blue/synthesis models should be selected.

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 states a specific action ('Execute'), a targeted resource type ('plan, design, or code snippet'), and a clear outcome ('critical flaws and mitigations'). The 'Red Team vs Blue Team' framing distinguishes it from sibling review tools without ambiguity.

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 phrase 'to identify critical flaws and mitigations' gives clear context for when the tool should be used, and the enumerated input types define acceptable targets. However, it does not explicitly compare against alternatives like coeus_second_opinion or coeus_counterfactual_review.

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