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Python
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video_apply_mask

Applies an image mask to a video, making masked areas transparent and feathering mask edges for clean compositing. Use it to isolate subjects or reveal layers in video.

Instructions

Apply an image mask to a video with edge feathering.

Args: input_path: Absolute path to the input video. mask_path: Absolute path to the mask image (white = visible, black = transparent). feather: Feather/blur amount at mask edges in pixels (default 5). output_path: Where to save the output. Auto-generated if omitted.

Input Schema

NameRequiredDescriptionDefault
featherNo
mask_pathYes
overwriteNoExplicitly allow replacing existing media. Existing non-media files are protected.
input_pathYes
output_pathNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.16.4
    • addedInput schema / properties / overwrite
      Added value: +{
+  "default": false,
+  "description": "Explicitly allow replacing existing media. Existing non-media files are protected.",
+  "title": "Overwrite",
+  "type": "boolean"
+}
  2. Changed1 schema field changedv1.16.0
    • addedInput schema / additionalProperties
      Added value: +false
  3. Addedv1.5.1

TDQS

B3.4/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It usefully discloses the mask convention (white = visible, black = transparent) and the feather default, and notes output auto-generation — real behavioral value. But it says nothing about whether audio/codec/quality are preserved, what happens on existing output files, or any performance constraints.

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?

Front-loaded single-sentence purpose followed by a tight Args list; every line carries information. Mild redundancy with parameter titles, but nothing wasteful.

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?

An output schema exists so return values needn't be described, and the description covers the inputs and mask semantics adequately for a filtered-render operation. The remaining gap is pipeline behavior (audio, container, quality) for a mutation tool with no annotations.

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

Parameters4/5

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

Schema coverage is only 20%, yet the description documents four of five parameters, including non-obvious semantics: absolute paths, white/black mask meaning, and feather units in pixels with a default. The undocumented 'overwrite' flag is at least covered by the schema's own description.

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?

States a specific verb and resource ('Apply an image mask to a video') plus the differentiator 'edge feathering'. It doesn't distinguish itself from nearby siblings like video_shape_mask, video_luma_key, or video_chroma_key, so an agent can't tell from the text alone which masking tool to pick.

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

Usage Guidelines2/5

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

No guidance on when to use this versus the many alternative masking/compositing tools in the sibling list. Only inference available is 'mask image exists' from the parameter names.

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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