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Sample frames (contact sheet)

sample_frames

Create a tiled contact sheet of evenly spaced video frames with timestamps, enabling quick preview of video content before editing.

Instructions

Tile evenly-spaced frames from across the video into one image, each stamped with its timestamp. Use this to SEE what's in a video before deciding how to edit it — create the sheet, then view the image file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoHow many frames to sample (default 12)
columnsNoGrid columns (default 4)
input_pathYesPath to the source video
tile_widthNoWidth of each tile in pixels (default 320)
output_pathNoWhere to write the image
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It reveals the output is an image file, frames are evenly spaced and stamped with timestamps, and instructs to 'view the image file'. However, it does not mention whether the output path is overwritten, the creation side-effect, or any permissions needed. This is adequate but not exhaustive.

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, front-loaded with the action and result, then a clear usage note. Every sentence adds value: the first defines the function, the second explains when and how to use it. No redundancy or filler.

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?

For a medium-complexity tool with 5 parameters and no output schema, the description plus the well-documented schema provide enough information to invoke correctly. It explains the output (image), the sampling strategy (evenly-spaced), and the timestamp stamping. It doesn't cover edge cases like insufficient video length or overwrite behavior, but these are not critical for basic invocation.

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?

The input schema has 100% parameter coverage with clear descriptions, including defaults and ranges. The description adds no additional parameter-specific details beyond restating the purpose. Per the rubric, a baseline of 3 is appropriate when the schema handles 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 opens with a specific verb-resource pair: 'Tile evenly-spaced frames from across the video into one image', clearly indicating the tool creates a contact sheet. It also mentions timestamps, distinguishing it from extract_frame and video_from_images. This is unambiguous and differentiates the tool from sibling tools.

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 says 'Use this to SEE what's in a video before deciding how to edit it', giving a clear use case and temporal context. It does not name alternatives or exclusions, but the pre-edit exploration purpose is well communicated, which is sufficient guidance for an AI agent.

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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