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capcut_set_background_removal

Toggle background removal for a CapCut draft segment: use AI portrait matting, chroma key with a hex color, or turn matting off.

Instructions

Toggle background removal on an existing video clip in the CapCut draft.

  • mode: "smart_portrait" (CapCut's local AI model segments the person without a green screen) "chroma" (green screen removal with specified hex color and intensity) "off" (disables matting)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNosmart_portrait
intensityNo
draft_nameYes
segment_idYes
chroma_colorNo#00FF00

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does add real behavioral context by explaining what each mode does (smart_portrait's local AI segmentation without a green screen, chroma keying with hex color and intensity), which goes beyond the schema. It omits, however, whether the operation requires the segment to exist, reversibility, or any permission/auth considerations.

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 purpose is front-loaded in a single sentence and the mode options are presented as a compact list with no wasted prose. Structure is efficient, though the indentation is slightly irregular.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described. However, for a mutation tool with five parameters at 0% schema coverage and no annotations, the description leaves required parameters and behavioral constraints uncovered, falling short of full completeness.

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 0%, so the description must compensate. It documents the three 'mode' values and implies the roles of chroma_color and intensity, but leaves draft_name and segment_id (the two required params) entirely unexplained and never maps 'intensity' or the hex color to their parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource ('Toggle background removal on an existing video clip') and scopes it to the CapCut draft, which is unambiguous. It does not explicitly contrast itself with any sibling tool, but the function is distinct enough that an agent can identify its role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

It implies usage ('on an existing video clip' signals the clip must already exist) but gives no explicit when-to-use, when-not-to-use, or alternatives among the matting siblings. The mode list conveys selection semantics without framing them as usage guidance.

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