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extractKeyframes

Extract frame images from videos at custom intervals to analyze visual content, create thumbnails, or review specific timestamps without manually scrubbing through footage.

Instructions

Extract keyframe images from a locally downloaded video at regular intervals using ffmpeg. Requires the video to be downloaded first via downloadAsset. Does NOT do visual search or classification — produces raw frame images. [~30-60s, requires ffmpeg]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoIdOrUrlYesVideo ID or URL (must have a local video asset)
intervalSecNoExtract one frame every N seconds (default 30)
maxFramesNoMaximum frames to extract (default 20)
imageFormatNoOutput image format (default jpg)
widthNoImage width in pixels, height auto-scaled (default 640)
Behavior4/5

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

No annotations provided, but description carries substantial load: discloses external dependency (requires ffmpeg), execution duration (~30-60s), and output nature (raw frame images). Could specify if operation is idempotent or disk space implications.

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?

Four distinct information units in tight prose: action, prerequisite, negative capability, performance metadata. Every sentence earns its place. Front-loaded with core extraction purpose.

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?

Strong coverage for a processing tool with no output schema: workflow integration (downloadAsset), implementation detail (ffmpeg), timing, and sibling differentiation present. Missing only error condition details or explicit return value description.

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 coverage is 100% with complete parameter descriptions. Description reinforces semantics ('regular intervals' for intervalSec, 'locally downloaded' for videoIdOrUrl constraint) but schema does heavy lifting. Baseline 3 appropriate for high-coverage schemas.

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?

Clear specific verb (Extract) + resource (keyframe images) + method (ffmpeg) + scope (regular intervals). Distinguishes from visual analysis siblings (searchVisualContent, findSimilarFrames) by stating it 'Does NOT do visual search or classification'.

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

Usage Guidelines5/5

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

Explicit prerequisite workflow ('Requires the video to be downloaded first via downloadAsset') naming specific sibling tool. Negative constraint clarifies it's for raw extraction, not analysis. Clear when-to-use vs. alternatives.

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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