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fablecut_transcribe

Transcribe speech from timeline clips into timed transcripts to read interviews, find phrases, and cut them from the edit.

Instructions

What is said, word by word, with times — and text-based editing. Transcribes the clips' speech with Whisper in the editor (an open tab, else headless Chrome / Edge; the speech model downloads once, the audio never leaves the machine), keeps one transcript per file (analysis/transcripts/), and answers with the timeline's words as timed lines (timeline seconds), so you can read an interview, pick the good takes, or find where something is said. find:"phrase" (or a list) reports every place it is said — case, punctuation and spacing ignored, whole words only — with the exact span; cut:true then extracts each of them on the targeted tracks (or tracks), the words and the pause after them, last first, in one revision: later material moves up, linked stems stay in sync, locked clips stay put (lock the music bed first). A version is saved before a cut. Files already transcribed aren't done again unless again:true. Default clips: every video / audio clip with sound on the open timeline. mediaIds reads whole files instead (file seconds; no cut). The same as the editor's Transcript tab.

Input Schema

NameRequiredDescriptionDefault
toNoOnly words before this time
cutNoCut every match of `find` out (default false: only report)
findNoA word or phrase (or several) to find; matches are reported with their timeline spans
fromNoOnly words from this time on (timeline seconds; file seconds with mediaIds)
againNoTranscribe again even when a transcript exists (another model or language)
forceNocut: also cut through locked clips (only when the user asked)
modelNoWhisper model: base (default, 77 MB, quick) or small (250 MB, more accurate, slower)
whereNoWhere to transcribe: auto (default): an open editor tab, else headless · tab · headless
tracksNocut: the lanes to cut on (default: the targeted tracks)
clipIdsNoClips to transcribe and read (a video brings its linked stems). Default: every clip with sound on the timeline
timeoutNoSeconds to wait for the transcription (default 1800)
languageNoThe spoken language as a Whisper code (en, es, hi, ja, …) or auto (default: detected)
mediaIdsNoInstead of clips: whole files, read in file seconds (find works, cut doesn't)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses that Whisper runs locally, audio never leaves the machine, the model downloads once, transcripts are kept at analysis/transcripts/, cuts are revision-based with a saved version, later material moves up, linked stems stay in sync, locked clips stay put, and cutting is skipped for mediaIds.

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?

The core purpose is front-loaded in the first sentence, and most of the dense text earns its place for a 13-parameter tool. The long run-on sentences and heavy em-dash usage make it harder to scan than ideal, but the information density is justified.

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?

For a complex, unannotated tool with no output schema, the description covers workflow, defaults, side effects, local processing, and transcript storage well. It partially describes return values ('timed lines', 'exact span') but is less explicit about what cut mode returns after a revision.

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 description coverage is 100%, so the schema already documents all 13 parameters. The description reinforces semantics, such as mediaIds using file seconds and not supporting cut, and tracks defaulting to targeted tracks, but much of this duplicates the schema rather than adding substantial new per-parameter meaning.

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?

The description opens with a precise verb and resource: 'word by word, with times' and 'Transcribes the clips' speech with Whisper in the editor.' It distinguishes this tool from related siblings like fablecut_captions by emphasizing transcription plus text-based editing (find and cut), so an agent can identify its role 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 Guidelines4/5

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

It provides clear operational context: default clips are every video/audio clip with sound, mediaIds reads whole files instead, files already transcribed are skipped unless again:true, and 'lock the music bed first' before cutting. However, it does not explicitly compare or route against sibling tools such as fablecut_captions or fablecut_highlights.

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