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meet_ingest_chunk

Ingest live spoken lines into an active meeting session and flush each chunk to disk immediately, enabling real-time capture and durable storage for later processing.

Instructions

Ingests a live spoken line/chunk into an active session in real-time. Automatically flushes to disk immediately.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
speakerYes
session_idYes
relative_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add one meaningful behavior, 'automatically flushes to disk immediately', indicating persistence, but it omits critical operational details such as authentication requirements, failure behavior when no active session exists, whether chunks are appended, and whether calls are idempotent.

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?

The description is exactly two sentences with no filler. It front-loads the primary purpose and then adds a concise behavioral detail about immediate disk flushing; every word earns its place.

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

Completeness2/5

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

For a write operation with no annotations and 0% parameter documentation, the description is too thin to fully prepare an agent. It does not explain how to supply relative_seconds, what speaker values should look like, whether an active session must already exist, or what happens if the session is invalid.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It indirectly maps 'spoken line/chunk' to the text parameter and 'active session' to session_id, but it never explains the speaker or relative_seconds parameters, their formats, or semantics.

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 uses a specific verb ('ingests'), a specific resource ('live spoken line/chunk'), and a clear context ('active session', 'real-time'), which makes the tool's purpose unmistakable. It is distinguishable from sibling tools like fetch_google_transcript or export_minutes by its ingestion focus, though it does not explicitly name those alternatives.

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 'live spoken line/chunk into an active session in real-time' implies it should be used during an ongoing meeting, when streaming spoken content into the session. However, it gives no explicit guidance on when to prefer this tool over alternatives, nor does it state when not to use it.

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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