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CoReason-AI

coreason_multi_agent_debate

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by CoReason-AI

multiagentdebate

Facilitates structured debates among AI agents by coordinating registration, arguments, rebuttals, and judgments until a verdict is reached.

Instructions

Structured multi‑persona debate tool.

Call sequence (typical):

  1. Each persona registers once with action:"register".

  2. Personas alternate action:"argue" (fresh point) or "rebut" (counter a targetAgentId).

  3. A special persona (or either side) issues action:"judge" with a verdict text (first line should be "pro", "con", or "inconclusive").

  4. Set needsMoreRounds:false only when the debate is finished and a verdict stands.

Parameters:

  • agentId (string) : "pro", "con", "judge", or any custom ID

  • round (int ≥1) : Debate round number

  • action (string) : "register" | "argue" | "rebut" | "judge"

  • content (string, optional) : Argument text or verdict

  • targetAgentId (string opt.) : Agent being rebutted (only for action:"rebut")

  • needsMoreRounds (boolean) : True if additional debate rounds desired

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roundYes
actionYes
agentIdYes
contentNo
targetAgentIdNo
needsMoreRoundsYes
Behavior5/5

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

With no annotations provided, the description fully discloses the expected behavior: each persona registers once, alternates between argue/rebut, and a judge issues a verdict. It also clarifies the verdict format and termination condition, ensuring transparency about the tool's protocol.

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 well-structured with a numbered list and bullet points, making it easy to follow. Every sentence adds value without redundancy, achieving high conciseness while covering all necessary details.

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?

The description covers the protocol, parameter roles, and termination condition comprehensively. However, it does not mention what the tool returns or any output format, which could be helpful for an agent to interpret results. This minor gap prevents a perfect score.

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

Parameters5/5

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

The description adds significant meaning beyond the input schema, explaining each parameter's purpose, constraints (e.g., round >=1, action enum), and context (e.g., targetAgentId only for rebut). It also describes the special formatting for judge verdicts, compensating for the 0% schema coverage.

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 it is a 'Structured multi‑persona debate tool' and explains the primary purpose and flow of the tool. It specifies the actions (register, argue, rebut, judge) and their sequence, making the purpose distinct and comprehensible.

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

Usage Guidelines5/5

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

The description provides a detailed call sequence with steps for each persona, including when to register, argue, rebut, and judge. It explains the verdict format and when to set needsMoreRounds to false, offering clear guidance on proper usage.

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

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