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setWordText

Correct a single transcript word by its ID to fix misheard names or terms; captions update while the film and audio stay untouched. Use an empty string to blank a junk token.

Instructions

Correct ONE word's text, by the id getTranscriptWords returns. This changes the TRANSCRIPT and nothing else: the captions follow it, the film is untouched and no audio is cut. Use it when the transcriber misheard something — a name, a technical term — and the user asks for it to read correctly. Passing an empty string BLANKS the word: it keeps its place in the media but leaves the captions, which is how a junk token like "(inaudible)" is removed without cutting the speech around it. Writing the transcriber's own text back clears the correction. This is NOT how you make a spoken word go away — that removes only the label and leaves the film saying it; use removeWords, which cuts the audio with it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
wordIdYes
assetIdNo
projectIdNoThe project to act on, from listProjects. Omit it only for the project open in the OpenScreen editor, which works only while the app runs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.1

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (which only mark it as a non-readonly, non-open-world, non-destructive write), the description discloses what is mutated (transcript + captions, not film or audio), that an empty string blanks rather than deletes the word, and that restoring the original text clears the edit.

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?

It opens with the core action and scope before branching into edge cases and the contrast with removeWords. Every sentence carries distinct information, though the final removeWords contrast is slightly convoluted and adds length.

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?

No output schema exists, so the description appropriately covers the mutation semantics; with 4 params it covers text and wordId well and relies on the schema for projectId, but assetId's role is never addressed.

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 only 25% (only projectId documented), so the description must carry the rest. It richly defines the `text` parameter (empty = blank, original = clear) and points to getTranscriptWords as the source of wordId, but assetId is left completely unexplained.

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 and resource ('Correct ONE word's text') with a precise scope ('This changes the TRANSCRIPT and nothing else'), and explicitly distinguishes itself from removeWords. An agent can select it correctly without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when ('Use it when the transcriber misheard something — a name, a technical term'), a when-not ('This is NOT how you make a spoken word go away'), and names the alternative (removeWords) with the reason it differs (it cuts audio).

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