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Detect scene changes

detect_scenes

Identify scene changes in a video by detecting abrupt picture cuts. Returns timestamps you can use to split or re-edit clips with trim_video or concat_videos.

Instructions

Find timestamps where the picture changes abruptly (cuts between scenes/shots). Returns a list of cut times you can feed into trim_video/concat_videos to split or re-edit the video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thresholdNoSensitivity 0.1–1; lower finds more cuts (default 0.4)
input_pathYesPath to the source video
Behavior4/5

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

With no annotations, the description carries the burden. It clearly states that the tool returns a list of cut times, implying a read-only analysis. It adds useful context about what constitutes a scene change ('picture changes abruptly') and how the output is consumed. While it doesn't discuss computational cost or exact threshold behavior (schema covers threshold), it is transparent enough for a detection tool.

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?

Two sentences with zero waste. The verb-led opening ('Find timestamps') immediately conveys the action, followed by the return type and a clear use case. Every word earns its place.

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

Completeness5/5

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

For a simple 2-parameter tool with no output schema, the description is complete. It covers the tool's purpose, what it returns, and how the result should be used (feeding into trim_video/concat_videos). No critical information is missing for an agent to select and invoke the tool correctly.

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%, with both parameters (input_path and threshold) already well-described in the schema. The description adds the conceptual link between threshold and 'abrupt' changes but doesn't provide additional syntax or format details. Baseline 3 is appropriate since the schema does the heavy lifting.

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?

The description uses a specific verb ('Find') and resource ('timestamps where the picture changes abruptly'), clearly identifying this as a scene-cut detection tool. It distinguishes from sibling tools like detect_silence (audio) and from editing tools by explicitly framing the output as cut times for downstream splitting/re-editing.

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?

The description explicitly states the intended use: 'feed into trim_video/concat_videos to split or re-edit the video.' This gives clear context for when to invoke the tool. It doesn't mention when not to use it or alternatives, but the context is strong enough for selection.

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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