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lawriec
by lawriec

extract_frames

Extract evenly-spaced frames from a video as JPEG images, either for direct viewing via base64 or as saved files for batch analysis. Preview video content over time.

Instructions

Extract evenly-spaced frames from a video file as JPEG images. Returns the frames as base64 images that can be viewed directly. Useful for understanding what happens in a video over time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_timeNoEnd time in seconds (default: end of video)
file_pathYesAbsolute path to the video file
num_framesNoNumber of frames to extract (1-20, default 10). Frames are evenly spaced across the time range.
output_dirNoIf provided, save frames as JPEG files to this directory instead of returning base64 images. Returns file paths and timestamps as text. Useful for batch processing where you don't want images in the response.
start_timeNoStart time in seconds (default: beginning of video)
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 that frames are returned as base64 images that can be viewed directly, which is a key behavioral detail. However, it does not mention the output_dir alternative, potential performance implications, or error conditions. Given the lack of annotations, more behavioral context would be beneficial, but the core output behavior is disclosed.

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 two sentences, front-loaded with the action and output format, followed by a concise use case. Every word earns its place, with 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?

Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description covers the core purpose, output format, and intended use case. It does not mention the configurable time range or output_dir behavior, but those are fully described in the schema. The description is sufficiently complete for an agent to understand what the tool does and when to use it.

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 each parameter already well-documented. The description does not add material semantic value beyond reinforcing that frames are evenly spaced and returned as base64 images, which aligns with the num_frames and output_dir parameters. The schema already carries the parameter semantics, so the description adds only marginal value.

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 tool's action: 'Extract evenly-spaced frames from a video file as JPEG images.' It specifies the resource (video file), output format (JPEG), and sampling strategy (evenly-spaced). This distinguishes it from sibling tools like extract_frame_at_timestamp, which extracts a single frame at a specific timestamp.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a use case: 'Useful for understanding what happens in a video over time.' This implies when to use it but does not explicitly state when not to use it or mention alternatives like extract_frame_at_timestamp or generate_thumbnail_grid. Usage guidance is present but not fully explicit.

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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