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Transcribe a local video

transcribe_video

Transcribe a local video file via any OpenAI-compatible speech-to-text API, producing a timestamped transcript and saving an .srt for uploads, captions, metadata, and chapters.

Instructions

Transcribe a video file on this computer with any OpenAI-compatible speech-to-text API (needs ffmpeg and a configured key). Saves an .srt you can pass to upload_video or upload_captions, and returns a timestamped transcript for writing metadata and chapters.

Input Schema

NameRequiredDescriptionDefault
languageNoSpoken language hint, e.g. "en".
file_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already flag readOnlyHint=false and openWorldHint=true; the description adds the value beyond them by naming the external dependency and credential requirement and disclosing the local side effect of writing an .srt file. It omits where the file is written, whether it overwrites, and any runtime/length limits.

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 dense sentences with the action, prerequisites, output artifact, and downstream use all front-loaded. No filler or redundancy.

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?

With no output schema, the description carries the return-value burden and does so (timestamped transcript plus an .srt). Prerequisites and downstream chaining are covered; only path conventions and error/failure behavior are absent, which is acceptable but not exhaustive for a tool that shells out to ffmpeg and a remote API.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: 'language' is documented in the schema, but 'file_path' has no description there. The description only implies a local path via 'on this computer' and adds no format, path-style (absolute vs relative), or supported-container details, so it does not compensate for the gap. Baseline 3 applies.

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+resource ('Transcribe a video file on this computer') and scopes it to a local file, which cleanly separates it from the upload/generate_metadata siblings that operate on the remote platform. The dual output (an .srt on disk plus a returned timestamped transcript) is named explicitly.

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 concrete preconditions ('needs ffmpeg and a configured key') and a downstream workflow pointer — the .srt can be fed to upload_video or upload_captions, and the transcript is for 'writing metadata and chapters', routing to generate_metadata. No explicit when-not or failure-handling guidance, so not a 5.

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