Skip to main content
Glama

get_saved_transcript

Read-onlyIdempotent

Retrieve a saved transcript’s text by ID in paginated chunks, including total length and next offset so you can read or process long transcripts incrementally.

Instructions

One saved transcript's text, in pages (default 20,000 characters). The result says the total length and the next offset. Text is wrapped in . Returned text is sent to the AI model you are using.

Input Schema

NameRequiredDescriptionDefault
idYesThe id from list_saved_transcripts.
limitNo
offsetNo
streamNameNoStream name. Defaults to CONFCAP_STREAM, or the owner's only stream.
includeHiddenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the safety profile is covered. The description adds genuine context beyond that: the default page size of 20,000 characters, that total length and next offset are returned, and that text is wrapped in <untrusted-text> and forwarded to the model — an important trust-boundary disclosure. It stops short of describing behavior for edge cases like missing transcripts.

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?

Front-loaded with the core purpose and page size, followed by return-value and trust caveats. Sentences are short and mostly earn their place, though the final 'Returned text is sent to the AI model you are using' is somewhat redundant with the preceding untrusted-text warning.

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

Completeness3/5

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

There is no output schema, so the description responsibly explains the return shape (total length, next offset, wrapped text). But for a 5-parameter tool with 40% schema coverage, key semantics — how to choose a stream, what includeHidden reveals — are absent, so an agent could call it correctly only for the common single-stream case.

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?

With only 40% schema description coverage, the description partially compensates by explaining the default page size (limit) and the returned next offset (offset), plus the <untrusted-text> wrapper. But it says nothing about streamName or includeHidden, which are undocumented in the schema as well, leaving half the parameters ambiguous.

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?

States a specific verb+resource: retrieves the text of one saved transcript, in pages. It is distinguishable from list_saved_transcripts (which enumerates transcripts) by its singular focus and its mention of paginated text. It does not explicitly name or contrast with sibling tools like get_live_captions, so it falls short of a 5.

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 mention that 'the result says the total length and the next offset' implies the pagination workflow, so an agent can infer to call repeatedly with offset. However, there is no explicit guidance on when to use this versus get_live_captions or how to obtain the id (that only appears in the schema's id description). Usage is implied rather than stated.

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