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video_thumbnail

Extract a single frame from a video at a specified timestamp to create a thumbnail image. Specify input video path, optional timestamp, and output path for the frame.

Instructions

Extract a single frame (thumbnail) from a video.

Args: input_path: Absolute path to the input video. timestamp: Time in seconds to extract frame. Defaults to 10% of video duration. output_path: Where to save the frame image. Auto-generated if omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_pathYes
timestampNo
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 discloses key behavioral traits: it extracts a frame, uses a default timestamp (10% of duration), and auto-generates output paths if omitted. However, it lacks details on file formats, error handling, performance, or permissions needed for file access, leaving gaps in behavioral context.

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?

The description is appropriately sized and front-loaded, starting with the core purpose in the first sentence, followed by a structured Args section that efficiently explains each parameter. Every sentence adds value without redundancy, making it easy to scan and understand quickly.

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 the tool's moderate complexity (3 parameters, no annotations, but has an output schema), the description is fairly complete. It covers the purpose and parameters well, and since an output schema exists, it doesn't need to explain return values. However, it could improve by addressing behavioral aspects like error cases or supported formats to be fully comprehensive.

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?

With 0% schema description coverage, the description must compensate, and it does so effectively by explaining all three parameters: input_path ('Absolute path to the input video'), timestamp ('Time in seconds to extract frame. Defaults to 10% of video duration'), and output_path ('Where to save the frame image. Auto-generated if omitted'). This adds crucial meaning beyond the bare schema, though it could include more details like supported video formats.

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 clearly states the specific action ('Extract a single frame (thumbnail) from a video') with the resource ('video'), distinguishing it from sibling tools like video_info, video_trim, or video_convert that perform different operations on videos. It precisely defines what the tool does without 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 provides no guidance on when to use this tool versus alternatives. With many sibling video tools available (e.g., video_storyboard for multiple frames, video_preview for previews), it doesn't specify scenarios where thumbnail extraction is preferred or when other tools might be more appropriate. Usage is implied but not explicitly stated.

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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