moamcp

by Yorha9e

Overview Schema Source Related Servers Discussions Admin

TypeScript

Local

moa_start_debate

Seed a multi-agent debate with reference results to set the initial state and start the round-robin discussion.

Instructions

Seed the debate state machine {turn:1, round:1, speaker: first agent} with reference results.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>",
      "reference_results": "<reference_results>"
    },
    "name": "moa_start_debate"
  }
}

Input Schema

Name	Required	Description	Default
`task_id`	Yes	MOA task id
`reference_results`	Yes	Reference Pool results, passed through to agents as context

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 28, 2026

TDQS

A3.6/5.0

Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It reveals the initial state and reference results passing, but omits critical facts such as side effects, idempotency, error handling, or what happens if the tool is called multiple times. The description lacks depth for a mutation tool.

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, well-structured sentence with no wasted words. It front-loads the key information about the state machine initialization and reference results. It perfectly balances brevity with informativeness.

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 the tool has no output schema, the description does not explain what the tool returns or how to interpret the result. It also does not mention any side effects or interaction with other debate tools. For a tool that likely produces an output (e.g., a debate ID or status), this is a significant gap.

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?

The schema already describes both parameters (100% coverage). The description adds context for reference_results by stating they are 'passed through to agents as context,' which clarifies their role beyond the schema's generic description. This adds meaningful value for an agent selecting parameters.

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 that the tool seeds the debate state machine with specific initial values (turn:1, round:1, speaker: first agent) and reference results. The verb 'seed' and explicit state machine details make the purpose unambiguous and distinguish it from siblings like moa_init or moa_submit_turn.

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

Usage Guidelines3/5

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

The description implies that this tool is used after preparing reference results and before agents start debating, but it does not provide explicit guidance on when to use it versus alternatives like moa_init. There is no mention of prerequisites, exclusions, or sequence relative to sibling tools.

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