Detect scene changes in videos by analyzing frame differences, with optional AI-assisted detection and adjustable thresholds for identifying cuts and transitions.
Detect scene changes in video.
| Name | Required | Description | Default |
|---|---|---|---|
| use_ai | No | ||
| overwrite | No | Explicitly allow replacing existing media. Existing non-media files are protected. | |
| threshold | No | ||
| input_path | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.16.4Input schema / properties / overwriteAdded value: +{
+ "default": false,
+ "description": "Explicitly allow replacing existing media. Existing non-media files are protected.",
+ "title": "Overwrite",
+ "type": "boolean"
+}v1.16.0Input schema / additionalPropertiesAdded value: +falsev1.5.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full behavioral burden. It does not say whether detection is read-only or writes output media, what the overwrite flag protects, how use_ai changes behavior, or what performance characteristics apply; only the terse purpose is stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence with no filler and the purpose front-loaded. It is appropriately sized, though the brevity is also the source of its underspecification rather than a model of efficient completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 explained. However, with four parameters at 25% schema coverage and no annotations, the definition leaves too much unexplained for a tool that appears to produce media artifacts and has near-duplicate siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, with just the overwrite parameter documented in the schema. The description adds no meaning for threshold (default 0.3) or use_ai, which are the two parameters an agent most needs explained, so it fails to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific verb and resource: detecting scene changes in a video. It is clear what the tool does, but it does not differentiate itself from the near-identical sibling video_detect_scenes, leaving the agent unsure which scene-detection 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus video_detect_scenes, video_auto_chapters, video_find_moments, or video_inspect_temporal. No preconditions, exclusions, or alternative-routing advice are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.