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Glama

Who is in the meeting

get_meeting_state

Retrieves the current people list in a meeting room, including hand, microphone, and camera status reported by the Meeting Bot; optionally returns a PNG snapshot.

Instructions

Who is in the room, plus hand, microphone, and camera when Meeting Bot reports them. This is the people list. snapshot is the same list plus a PNG of the page. Contract version 1 returns the people list only.

Input Schema

NameRequiredDescriptionDefault
meeting_idYesThe meeting_id of the room (from create_broadcast or join_broadcast).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that hand, microphone, and camera states are returned only 'when Meeting Bot reports them,' and that contract version 1 returns the people list only. However, it omits other relevant behavior such as data freshness, failure modes, and whether the call is read-only or has side effects.

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 short and front-loaded with the core purpose: identifying who is in the room. Each sentence adds useful information, including the sibling distinction and version contract. It is efficient, though the contract version sentence is slightly cryptic without additional context.

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 read-only getter with one well-documented parameter and no output schema, the description explains the returned contents, conditional fields, alternative snapshot tool, and version-specific behavior. It lacks some detail about output structure and data freshness, but overall it provides enough context for an agent to invoke 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?

The schema has 100% description coverage for its single parameter, meeting_id, including its source from create_broadcast or join_broadcast. The description adds no additional parameter semantics beyond what the schema already provides. With high coverage and one simple parameter, the baseline of 3 is appropriate.

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?

The description clearly states the resource: the people list for a meeting, including hand, microphone, and camera status when available. It explicitly distinguishes itself from the snapshot sibling by noting snapshot is the same list plus a PNG. It is specific enough for an agent to identify the tool's output, though it phrases purpose as a question rather than a direct verb+resource 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 names the alternative snapshot tool and explains the condition for using it: snapshot provides the same people list plus a PNG of the page. This gives clear selection guidance between the two tools. It does not provide explicit exclusions or prerequisites, but the sibling contrast is strong enough for a 4.

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