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cut_take

Cut take segments into one clip with constant frame rate and in-sync voice; fix audio offset, move cut points off words, and output word timings.

Instructions

Cut takes into one clip: video at a constant frame rate, the voice in sync, and word times for the clip. It is the default for a cut of a take: it fixes the take's audio offset and frame rate, moves a cut point that falls inside a word to the word's edge (listed in 'moved'), and uses the take's clean voice when clean_voice is done. For what it cannot do (a J/L cut, a speed change, a cut inside a word, an effect), use your own ffmpeg on its clip and .wav, or on the take with get_session's audio_offset_s, and tell the user what you did. set_best_cut only marks a range; cut_take makes the video. Writes _work/-vN.mp4, .wav (voice only) and .words.json in the session. A short cut comes back done; a long one returns a job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionYesSession as 'Project/folder', an absolute path, or its id (from get_session). An old path still works after a rename or move.
segmentsYesThe parts to keep, in order: [{take, in, out}], seconds of the take. Add kind: 'screen' to cut a take's screen file. rough_cut's cut has this shape.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the sparse annotations, the description discloses critical behavior: it fixes the take's audio offset and frame rate, moves cut points inside words to the word's edge and lists them in 'moved', uses clean voice when clean_voice is done, writes specific output files, and returns either 'done' or a job depending on cut length. These are substantive operational details not captured by the annotations.

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 description is front-loaded with the core purpose and then layers in behavior, limitations, alternatives, and outputs. It is dense but every major point serves the agent; it is longer than a minimal description, though appropriate for a complex tool with no output schema.

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?

For a mutation tool with no output schema and only basic annotations, the description covers the important missing context: what it fixes, what it writes, length-dependent return behavior, edge-case handling, and alternatives when the tool cannot perform a requested edit.

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 session and the nested segment fields. The description repeats the segment shape and adds only that rough_cut's cut has the same shape, which provides mild contextual help but does not add syntax or constraints beyond the schema.

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 states a specific verb and resource: cutting takes into one clip with constant frame rate, synced voice, and word times. It explicitly distinguishes itself from set_best_cut by noting that set_best_cut only marks a range while cut_take makes the video.

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?

It identifies itself as the default for cutting a take and clearly lists when not to use it (J/L cut, speed change, cut inside a word, effect), directing the agent to use its own ffmpeg instead. It also names set_best_cut as a related alternative and explains the division of labor.

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