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Glama

Add subtitles/captions to a video

generate_subtitled_video

Render burned-in captions onto a video from a completed UGC job or a public video URL plus script, with caption style presets.

Instructions

Render burned-in captions onto a video. Provide either sourceJobId (a previously completed UGC job, whose video + script are reused) or both videoUrl (a public https video) and script (the spoken words). Choose a caption style with preset. Defaults to waiting for the result; set wait=false to return a job id to poll with get_job.

Input Schema

NameRequiredDescriptionDefault
waitNoWait for completion (default true).
presetNoCaption style preset (default classic_subtitle).
scriptNoThe exact spoken words to render as captions (with videoUrl).
videoUrlNoPublic https URL of the video to caption (with script).
sourceJobIdNoId of a completed UGC job to caption (reuses its video + script). Provide this OR videoUrl+script.

Output Schema

NameRequiredDescriptionDefault
jobNo
errorNo
resultNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations cover the safety profile (not read-only, not destructive, closed world), and the description adds genuinely new behavior: the tool renders burned-in captions and by default blocks until completion, with wait=false switching to a pollable job id. It does not mention render duration, cost, or failure modes, but the blocking/async disclosure is the key trait an agent needs.

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?

Four compact sentences, front-loaded with the action and then the input rules and async behavior. Nothing is padded, though the preset sentence ('Choose a caption style with preset') adds little beyond the schema's enum.

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

Completeness5/5

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

All five parameters are documented at 100% coverage, the input branching and async/wait behavior are explained, and an output schema exists so return values need not be restated. An agent has everything needed to call it correctly.

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 description coverage is 100%, so the baseline is 3; the description earns above that by explaining the relationship between parameters ('sourceJobId ... whose video + script are reused' vs. providing videoUrl and script together) that the flat schema cannot express.

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?

Opens with a specific verb+resource ('Render burned-in captions onto a video') that is unmistakable and cannot be confused with the generate_video / generate_ugc_video siblings. It never explicitly routes against those siblings, but the operation itself is self-differentiating.

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 mutual-exclusion rule for inputs ('either sourceJobId ... or both videoUrl and script') and a clear async branch (wait=false returns a job id to poll with get_job), naming the polling sibling. It stops short of saying when to prefer this over generating a fresh UGC job, so not a full 5.

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