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Glama

get_transcript

Retrieve the full timestamped transcript from a previously analyzed video without resending frames. Use it to quote or search long talks while conserving context.

Instructions

Return the full timestamped transcript of a video already analysed, without re-sending any frames. Use when you only need the words (quoting, searching a long talk) and the images would waste context.

Args: source: The same URL or path given to watch_video. max_chars: Truncate beyond this many characters (default 20000).

Input Schema

NameRequiredDescriptionDefault
sourceYes
max_charsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden and does disclose the key trait: content is served from an existing analysis with no frame re-sending, and max_chars truncates. What is left unstated is the failure mode when the source was never analysed (error vs. implicit fetch) and the exact timestamp format returned.

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?

Two front-loaded sentences covering purpose, use case and context economics, followed by a tight two-parameter args block. No sentence is filler and the differentiating claim (no frames re-sent) comes first.

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 two-parameter read tool with no output schema, the description covers purpose, prerequisite, cost rationale, and truncation. It only leaves the not-yet-analysed case and the precise return shape undefined, which are minor for this tool class.

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?

Schema coverage is 0%, so the description must compensate and largely does: 'source' is constrained to the same URL or path previously passed to watch_video, and max_chars is explained as a truncation threshold with the default. It does not clarify whether source accepts either URL or local path forms interchangeably.

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?

States a specific verb (return) and resource (full timestamped transcript) plus a scope qualifier: a video already analysed. It also implicitly distinguishes itself from get_frames ('without re-sending any frames') and from watch_video ('the same URL or path given to watch_video'), so an agent can route without opening schemas.

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?

Gives an explicit when-to-use condition — quoting or searching a long talk where images would waste context — and states the precondition that the video must already have been analysed. The alternative (get_frames / watch_video) is implied by the context-cost framing rather than named explicitly, keeping this just short of a 5.

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