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Generate captions

generate_captions

Auto-captions from the transcript onto a "Captions" text track (replaces existing). Presets: title, subtitle, caption, karaoke, boxed, neon, tiktok ("karaoke" highlights the spoken word).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_captions"
  }
}

Input Schema

NameRequiredDescriptionDefault
yNovertical offset from center in px (default lower third)
textNoText style
rangeNo
presetNo
maxCharsNo
maxWordsNo
projectIdNoProject to act on (default: the open one)
trackNameNo
uppercaseNo
maxDurationNo
highlightWordsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

The description adds real behavioral context beyond the annotations: it discloses that existing caption content is replaced and that output lands on a dedicated "Captions" track, and it explains that the karaoke preset highlights the spoken word. Minor tension with destructiveHint=false given the stated replacement, though the overwrite is scoped to one generated track; it still omits auth needs and what is returned.

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?

Two dense sentences, front-loaded with the core action and the replacement caveat before the preset list. The preset enumeration repeats the enum but is short enough to justify as quick orientation; nothing else is wasted.

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?

Incorrectly scored here for emphasis: for an 11-parameter, nested-schema, mutation tool with no output schema and an implicit transcript dependency, this description is too thin – it should at least flag that chunking parameters control caption segmentation and that a transcript is required. This is a significant gap for the tool's complexity.

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 only 27% across 11 parameters, including a 20+ property nested text style object, and the description compensates for almost none of it – range, maxChars, maxWords, maxDuration, trackName, projectId and y are untouched. The preset list it enumerates merely restates the schema enum, adding no meaning beyond it.

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 action and target: auto-generates captions from the transcript onto a "Captions" text track. This implicitly separates it from manual text tools like add_text, but it never mentions the closest alternative, voice_captions, so an agent cannot fully disambiguate from the sibling list alone.

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?

Usage is implied by the phrase "from the transcript" – you need an existing transcript and want timed captions. There is no explicit when-to-use/when-not, no statement of prerequisites (e.g. that transcribe_media must run first), and no routing versus add_text or voice_captions.

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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