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glitch_depth_splatting

Apply a depth-based point splatting effect to video by extracting pseudo-depth from luminance and rendering scattered points for a 3D particle-like appearance.

Instructions

Apply depth-based point splatting effect (requires Node.js + GPU).

Extracts pseudo-depth from luminance and renders the image as scattered points, creating a 3D particle-like appearance.

Args: input_path: Absolute path to input video. output_path: Absolute path for output video. depth_scale: Depth extraction intensity. Default 1.0. spread: Point spread distance in pixels. Default 10.0. point_size: Size of each splatted point. Default 3.0. threshold: Depth cutoff threshold (0-1). Default 0.5.

Returns: Dict with success status and output_path.

Input Schema

NameRequiredDescriptionDefault
spreadNo
overwriteNoExplicitly allow replacing existing media. Existing non-media files are protected.
thresholdNo
input_pathYes
point_sizeNo
depth_scaleNo
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?

With no annotations, the description carries the full burden. It discloses the Node.js + GPU requirement and explains the algorithmic effect, which is useful. However, it omits mutating behavior details (e.g., overwrite protection, error handling, or processing side effects) that an agent would need for safe invocation.

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 effect and prerequisite, followed by a parameter list and return note. It is appropriately sized for a seven-parameter tool and avoids filler, though the 'Args:'/'Returns:' docstring style adds slight verbosity.

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?

Given an effect tool with seven parameters, no annotations, and an output schema, the description covers the effect, prerequisite, parameter meanings, and return format. It is nearly complete; only the overwrite safety behavior is not mentioned, but that is documented in the schema.

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 description coverage is only 14%, so the description must compensate. It documents six of seven parameters with clear semantics (depth extraction intensity, pixel spread, point size, threshold range), adding substantial meaning beyond the schema. The only gap is the overwrite parameter, which is already described in the schema.

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 clearly states a specific verb ('Apply') and resource ('depth-based point splatting effect') and explains the visual result. However, it does not explicitly differentiate this tool from the closely related sibling 'glitch_point_cloud', which could cause ambiguity.

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?

The description includes an environment prerequisite ('requires Node.js + GPU') but provides no guidance on when to choose this effect over alternatives like glitch_point_cloud or other glitch tools. There are no when-to-use or when-not-to-use statements.

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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