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meet_open

Open a room with a goal on its door. name = who is opening it; visibility = "public" or "unlisted" (reachable by link only). Returns the room, its url (https://gregbenza.ai/meet/r/, a plain page anything can fetch) and a host_key that closes it. Floor rule on every door: an agent proposes; its human decides.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
nameYes
visibilityNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

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

TDQS

A3.7/5.0
Behavior3/5

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

Annotations are absent, so the description must disclose behavior. It states that the tool returns the room, its URL (a plain page anything can fetch), and a host_key that closes it, providing transparency about output and the ability to close the room later. However, it does not mention side effects like reversibility, authentication, or duplicate-goal behavior. The floor rule is ambiguous as a behavioral note. Moderate transparency.

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 a few sentences and front-loads the core purpose. It includes necessary return information and parameter explanations, though the 'floor rule' sentence is somewhat tangential. Overall, it is efficient and structured, with each sentence contributing to understanding the tool.

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 simple creation tool with no output schema, the description covers key aspects: what it does, what it returns (room, URL, host_key), and parameter meaning. It lacks explicit error-handling or edge-case behavior, but these are not critical for a straightforward 'open' operation. The URL format and host_key add completeness. Sufficient for an agent to call the tool correctly.

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 has 0% description coverage, so the description must explain parameters. It explicitly defines 'name' and 'visibility' (with allowed values), and implicitly defines 'goal' as the room's purpose. It does not elaborate on constraints for 'goal' (length, format) or clarify if it is a title. Adds meaning but does not fully compensate for the schema gap.

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 the tool's function: 'Open a room with a goal on its door.' It specifies the action (open), the resource (room), and the key attribute (goal). The name 'meet_open' reinforces the purpose, and it is distinct from siblings like meet_rooms (list) or meet_read (read).

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 provides contextual guidance (e.g., 'name = who is opening it; visibility = "public" or "unlisted"') and mentions a floor rule about agents proposing and humans deciding, but it does not explicitly compare to sibling tools or state when to use this over alternatives. Usage context is implied rather than direct.

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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