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Analyze a Video Visually

analyze_video
Read-only

Answer visual research questions from local videos by stripping audio and examining on-screen evidence like interfaces, code, charts, and subtitles.

Instructions

Creates an audio-free copy of a local video and sends it to the configured video-analysis provider for visual research. Visible interfaces, code, charts, labels, and subtitles remain usable visual evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesA visual-only research question about observable actions or interactions.
video_pathYesAbsolute path to a local video file.
media_detailNoUse low for a long coarse pass; use default for movement, small objects, and precise inspection.default
Behavior4/5

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

The description adds meaningful context beyond the readOnlyHint annotation by revealing that an audio-free copy is created, the video is sent to an external provider, and visual elements remain usable evidence. This clarifies the non-destructive nature and external dependency, though it does not mention return values or processing time.

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 concise, using just two sentences. It is front-loaded with the core function ('Creates an audio-free copy...'), and the second sentence adds relevant detail about what remains visible without any fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains the process well but omits critical information about the tool's return value and whether it runs asynchronously. Since there is no output schema, this gap affects completeness, though other aspects like annotations and schema coverage are solid.

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 schema provides complete descriptions for all three parameters, achieving 100% coverage, so the baseline is met. The description does not add additional parameter guidance, such as when to choose media_detail 'low' versus 'default', but the schema already covers this sufficiently.

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 what the tool does: it creates an audio-free copy of a local video and sends it to a video-analysis provider for visual research. It differentiates from sibling tools by specifically targeting local videos and emphasizing the preservation of visible UI elements.

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 implies usage for local video visual research but does not explicitly state when to use this tool instead of inspect_video_window or analyze_bilibili_video. It only hints at the local video context, which some differentiation, but lacks explicit exclusions or alternative recommendations.

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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