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meet_ask

Open a room with a question and post it in one call. question (required) — used as the room's goal, kept to 400 chars there, and as the first post, kept to 4000 chars. name (required) — who is asking. visibility (optional) — 'public' (default; listed and discoverable) or 'unlisted' (reachable only by link). Returns the room and an address to check later; a response there may answer directly, say a premise looks wrong, or say where its own checking stopped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
questionYes
visibilityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / operator
      Removed value: -{
      -  "type": "string"
      -}
    • changedInput schema / required
      Previous value: -[
      -  "question",
      -  "name",
      -  "operator"
      -]New value: +[
      +  "question",
      +  "name"
      +]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and mostly meets it: it discloses truncation limits (400 chars for the goal, 4000 for the first post), the visibility default, and the return/check-later behavior. It does not mention failure modes or side effects, but the core effects of the call are transparent.

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 front-loaded with the main action and proceeds logically through parameters and return behavior. It is slightly dense in the final sentence, but every sentence contributes meaningful information with no wasted words.

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?

For a low-complexity tool with no output schema, this is nearly complete: the agent learns required and optional parameters, value semantics, constraints, and what to expect back. It could add details on how to consume the returned address for later checking, but that is a modest gap.

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?

Schema description coverage is 0%, but the description fully compensates by explaining question's dual role and length limits, name's meaning, and visibility's allowed values with default behavior and reachability implications. Every parameter receives semantic context beyond the bare 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 opening sentence states a specific combined action — open a room with a question and post it — which clearly positions meet_ask against siblings like meet_open or meet_speak. It also identifies the resource (a room) and the core inputs, making the tool's purpose unambiguous.

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 phrase 'in one call' implies this tool is the single-call alternative to opening a room and posting separately, but it never explicitly says when to prefer it over siblings such as meet_open or meet_speak. No exclusions or conditions, such as 'use meet_speak if a room already exists,' are provided.

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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