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get_video_frames_json

Extract evenly spaced frames from a video as base64 JPEGs with timestamps, enabling HTML galleries and visual skills to inspect specific video segments.

Instructions

Frames of a video as base64 JPEG with timestamps, for HTML galleries and skills. Same parameters, gate (confirm above 12) and cap (120) as get_video_frames. Read-only.

Args:
    asset_id: The video asset's UUID.
    count: Frames evenly spaced over the segment (default 6). Ignored when interval > 0.
    size: 'thumbnail' (250px, ~1.6k tokens per frame) or 'preview' (1440px, ~6.4k). Default 'thumbnail'.
    start: Segment start in seconds (default 0).
    end: Segment end in seconds (0 = to the end).
    interval: One frame every N seconds instead of count (1 = one per second, the maximum granularity).
    confirm: Required (true) when more than 12 frames would be produced; ask the user first.

Returns: JSON {asset_id, duration, backend, count, frames:[{timestamp, data, type}]},
a confirmation plan {confirm_required, frames_planned, estimated_tokens, ...}, or {"error": ...}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
sizeNothumbnail
countNo
startNo
confirmNo
asset_idYes
intervalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and handles it well: it states read-only behavior, the confirmation gate above 12 frames, the 120-frame cap, parameter interactions (interval overrides count), and the exact return shapes including confirmation and error objects. This is unusually thorough behavioral disclosure.

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 front-loaded with a one-sentence summary, then organized into Args and Returns sections. Every line carries needed information: parameter semantics, defaults, constraints, and output structure. It is dense but not bloated, and the structure makes it easy to scan.

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?

Given seven parameters, zero schema descriptions, and no annotations, the description covers all necessary invocation details, including the confirmation flow and return shapes. The presence of an output schema reduces the need to document return values, yet the description still provides an accurate summary, making the tool fully self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates by documenting every parameter with type, default, meaning, and constraints. It adds valuable semantics like '600px preview is ~6.4k tokens per frame' and 'interval is mutually exclusive with count', which the bare schema cannot convey.

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 returns video frames as base64 JPEGs with timestamps, which is specific and distinguishes it from the sibling get_video_frames. It also names the intended use cases (HTML galleries and skills) and explicitly references the sibling to clarify the relationship.

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?

It provides clear context for when this tool is appropriate by mentioning HTML galleries and skills, and by framing it as a read-only JSON-returning variant of get_video_frames. It does not explicitly state 'use this instead of get_video_frames when...', but the intended use is clear enough without exclusions.

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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