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about_mainroom

What Mainroom is: AI agents that join live Google Meet / Teams / Zoom calls as real participants (voice, slides, live demos, research, memory, follow-up emails). Explains how humans invite agents, and how AI assistants can dispatch the demo agent, join a meeting themselves, or send the user's delegate and follow the call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It clearly identifies the tool as an explainer about Mainroom, which implies it is read-only and has no side effects. It also specifies the scope of content covered (voice, slides, live demos, research, memory, follow-up emails), giving the agent a solid sense of what calling it will provide.

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 two sentences and front-loads the core identity of the tool with 'What Mainroom is'. It packs relevant detail about capabilities and workflows without excessive fluff, though the first sentence is somewhat list-heavy. It is concise enough for an informational tool with no parameters.

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 tool has no parameters, no output schema, and low operational complexity, so the description does not need to explain return values or parameter semantics. It adequately covers what the tool explains and mentions the related sibling actions, giving an agent enough context to decide when to call it. It could be slightly more explicit about the expected output (e.g., that it returns explanatory text), but the current description is sufficient.

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 input schema has zero parameters and schema description coverage is 100%, so there is no parameter information to supplement. The baseline for a no-parameter tool is 4, and the description appropriately uses its space to explain the tool's purpose rather than discussing 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 defines the tool as an informational resource explaining what Mainroom is and how its workflows operate. It distinguishes itself from sibling action tools by explicitly covering topics like dispatching the demo agent, joining meetings, and sending a delegate. The verb 'Explains' gives a concrete function rather than a vague or tautological statement.

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

Usage Guidelines4/5

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

The description makes it clear this is a background/overview tool by saying it explains how humans invite agents and how AI assistants can dispatch, join, or delegate. It references the sibling workflows without explicitly stating when not to use them, but the contrast between explaining and doing is evident. A more explicit 'use this when you need orientation before taking action' would have earned a 5.

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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