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Transform Clip

lab_transform

Relight and restyle an EXISTING clip while the performance stays untouched (Beeble Switch X): lighting, background and props change, the subject and its motion do not. The source is the clip of a generated-video row — or, with asset_id, an uploaded file that stands in for it. in_sec/out_sec cut the source server-side first, so a long take can be transformed in pieces. ASYNCHRONOUS: a new video row comes back as pending; poll it with lab_job_status. Costs credits when called without get_cost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
in_secNoCut the source server-side before it reaches the provider: start of the excerpt, in seconds. Only together with out_sec. What is billed is the MEASURED length of the cut, not out_sec minus in_sec.
out_secNoEnd of the excerpt, in seconds. Must lie behind in_sec; both are set together or neither.
asset_idNoR2 asset key of an uploaded video (the `key` from lab_list_assets, asset_type 'video') to transform INSTEAD of the row's own clip. The row from video_id still supplies project and scene; only the pixels come from the asset. The key must belong to that same project.
get_costNo`true` returns the published rate per unit and your balance WITHOUT transforming and without spending anything — NOT a total. Switch X charges by the MEASURED length of the source, which only the server knows before the run, and it is not priced from the lab_list_models catalog (that covers generation models). The real amount comes back with the actual call.
video_idYesGenerated-video id (from lab_animate/lab_job_status/lab_review_queue) — positive integer as string. ALWAYS required, also together with asset_id: this row anchors the run (project, scene, billing) and the backend answers 404 without it.
alpha_modeNoHow the subject is cut out from its background. Omit to let the backend decide ('auto'); the other modes fill, take a supplied matte, or work on a selection.
resolutionNoOutput tier of the transform. This is Switch X's OWN tier list, not one of the video-model resolutions in lab_list_models — that catalog covers generation models and has no entry for this path. The tier drives the price; omit it for the backend default.
transformation_promptYesWhat the clip should look like afterwards — light, place, props. The subject and its performance are preserved by the model; describing them again does not help.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false and destructiveHint=false. The description adds substantial context: asynchronous execution, a pending row as the return, polling via lab_job_status, credit cost unless get_cost is used, server-side cutting, and required video_id anchoring even with asset_id.

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?

Front-loads the core purpose, then covers source, cutting, async, and cost in five dense sentences. Every sentence earns its place for a complex tool; no redundant or filler content.

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, and the description explains the return behavior (new pending row, poll with lab_job_status) plus cost handling. It is complete enough for an agent to invoke correctly, though it omits failure/retry details beyond the 404 note.

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 eight parameters in detail. The description contextualizes in_sec/out_sec and asset_id but adds no syntax or meaning beyond what the schema provides; 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 and resource (relight/restyle an existing clip), names the model (Beeble Switch X), and distinguishes the operation from generation by emphasizing that subject and motion are preserved. It also clarifies source options, so an agent can identify it 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?

Explains when to use it (existing clip, performance untouched) and how to source the input (generated-video row or asset_id). It names lab_job_status for polling and get_cost for a no-spend preview, but does not state when to choose this over sibling transform tools like lab_prompt_transform or lab_vfx.

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

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