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mm_analyze_video

Read-onlyIdempotent

Analyze videos by extracting key frames and transcribing audio, producing a timeline summary with scene insights.

Instructions

抽帧分析视频,并可结合音轨转写。

Args: video_path: 本地视频绝对路径,支持 MP4/MOV/MKV/WEBM。 max_frames: 均匀抽取的帧数,1-20,默认 6。 include_audio: 是否同时转写音轨,默认 true。 question: 可选,分析关注点。

Returns: str: Markdown 格式的场景摘要(帧时间线 + 音轨转写)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNo
max_framesNo
video_pathYes
include_audioNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare read-only and idempotent behavior. The description adds meaningful context about the return format (Markdown scene summary), the uniform frame extraction behavior, and the default to include audio transcription, which goes beyond basic safety annotations. No contradiction found.

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: one-sentence summary followed by a structured list of arguments and return value. Every sentence and field adds value, 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 complexity and the schema lacking param descriptions, the description covers all parameters, return format, and core behavior. It does not mention time/resource limitations (e.g., video size limits), but annotations cover safety aspects, so the overall context is sufficient for an agent to invoke the tool correctly.

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%, but the Args section fully documents each parameter: video_path (local absolute path, supported formats), max_frames (range 1-20, default 6), include_audio (default true), and question (optional focus). This completely compensates for the missing schema descriptions.

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?

Description clearly states it extracts frames from video and optionally transcribes audio, distinguishing it from sibling tools like mm_describe_image (single image) and mm_transcribe_audio (audio-only). The verb '分析视频' (analyze video) with specific resources and capabilities makes the purpose unambiguous.

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?

Usage context is implied: it's for video analysis with frame extraction and optional audio transcription. However, it does not explicitly mention when to use this tool instead of alternatives (e.g., audio-only tasks should use mm_transcribe_audio), nor does it mention exclusions or prerequisites.

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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