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get_transcript

Read-only

Transcribe English speech from a local video (max 180s) with optional trim; returns source-timed text for review or correction.

Instructions

Transcribe English speech in one local video (up to 180 seconds) using an English speech model on your computer. Optional in/out trim seconds; returned line times are source seconds. The transcript text is returned to your assistant/provider, so call only when the user wants to review or correct it. Media and transcript are never sent to Modisign. First use downloads the speech model; later calls work offline. Use captions.corrections in edit_video to fix names/phrases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inNo
outNo
pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only cover the safety profile (readOnly, non-destructive), while the description adds substantial context the annotations cannot convey: media and transcript are never sent to Modisign, the transcript is surfaced to the assistant/provider, the first call downloads the speech model and later calls work offline, and returned line times are in source seconds. This is exactly the extra behavioral load the description should carry.

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?

Every sentence earns its place: purpose and limit first, then parameter semantics, then privacy/output routing, then the when-to-call constraint, then the model-download behavior, then the sibling alternative. No filler or repetition.

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?

There is no output schema, and the description covers the return contract (transcript text delivered to the assistant, line times in source seconds) plus runtime behavior (model download, offline operation, 180s cap). Nothing an agent needs to invoke this correctly appears to be missing.

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 it explains the two non-obvious parameters: 'in/out' are optional trim seconds, and returned line times remain referenceable to source seconds. 'path' is left unaddressed but its meaning is self-evident from the name; a note on path format/resolution would be needed for a 5.

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 ('Transcribe English speech in one local video'), including the hard 180-second scope and the local/English-only constraint. It also differentiates itself from the sibling edit_video by routing corrections to 'captions.corrections', so an agent can distinguish it without opening any schema.

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 a clear usage condition ('call only when the user wants to review or correct it') and names the alternative path for fixing names/phrases (edit_video captions.corrections). It stops short of stating when transcription is unnecessary (e.g. video already has captions), so it is strong but not a complete decision rule.

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