@argosvix/mcp-server

reply_proposal

Post a question about a proposal to receive an AI-generated explanation, simulating an inbox conversation without executing any actions.

Instructions

Post a question about a proposal and get the AI's reply (same as the inbox conversation). Explanation only — nothing is executed. Get proposalId from list_proposals.

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": {
      "proposalId": "<proposalId>",
      "body": "<body>"
    },
    "name": "reply_proposal"
  }
}

Input Schema

Name	Required	Description	Default
`body`	Yes	Question about the proposal (e.g. why did it degrade? should we fix it?)
`proposalId`	Yes	Target proposal ID (from list_proposals)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.30.0-alpha.14Jul 8, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries full burden. It discloses the tool is non-executing ('nothing is executed'), which is key. However, it omits other details like authentication needs, rate limits, or side effects, leaving some transparency gaps.

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?

Extremely concise: two sentences and a brief instruction. No redundant words, front-loaded with the main action and key differentiator ('explanation only'). Every sentence earns its place.

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

Completeness3/5

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

Given no output schema, the description is vague about the return value ('get the AI's reply'). Mentioning 'same as the inbox conversation' helps but doesn't specify format or structure. For a simple query tool, it is adequate but could be more complete.

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% with descriptions for both parameters. The description adds value by providing an example for 'body' (e.g., 'why did it degrade?') and a source hint for 'proposalId' ('from list_proposals'), improving agent understanding beyond the schema.

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

Purpose4/5

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

Clearly states the action ('post a question about a proposal') and the resource ('proposal'), with a specific outcome ('get the AI's reply'). The 'same as the inbox conversation' and 'explanation only' differentiate it from sibling tools like get_proposal_thread and propose_eval_criteria, though not fully explicit.

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?

Provides a prerequisite ('Get proposalId from list_proposals') and a behavioral note ('nothing is executed'), but lacks explicit guidance on when to use or avoid this tool versus alternatives (e.g., get_proposal_thread for just viewing).

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

Deploy Server