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smart_clip_tool

Automatically detects highlight segments in long videos such as vlogs, podcasts, and livestreams, then produces platform-adapted short clips with optional subtitles and background music.

Instructions

从长视频中自动识别精彩片段并裁切输出。适用于口播、播客、直播回放等语音驱动内容。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_pathYes输入视频文件路径
intentNo剪辑意图,自然语言描述。如:'提取最精彩的5个片段' / '找出所有金句'提取精彩片段
clip_countNo期望输出的片段数量
clip_duration_minNo单片段最短秒数
clip_duration_maxNo单片段最长秒数
platformNo目标平台 (auto/tiktok/youtube_shorts/instagram_reels/youtube/original)original
with_subtitlesNo是否烧录字幕
with_bgmNo是否添加背景音乐
output_dirNo输出目录./smart-clip-output

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries full burden. It discloses the core behavior (auto-identify and clip) but does not detail side effects (e.g., non-destructive), required permissions, or limitations. Adequate but not comprehensive.

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 extremely concise: two short sentences with key information front-loaded. No unnecessary words.

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?

Given the complexity (9 parameters, sibling tools) and lack of annotations, the description is minimal. It covers basic purpose but lacks context on how it differs from sibling tools like highlight_reel_tool. Output schema exists, so return values are covered elsewhere.

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%, so the schema already documents all parameters. The tool description adds no extra parameter information, meeting the baseline expectation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool identifies highlights and clips them from long videos, with examples of suitable content types. However, it does not explicitly differentiate from sibling tools like highlight_reel_tool.

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 provides context on when to use (voice-driven content) but lacks guidance on when not to use or mention alternatives, which would help for sibling differentiation.

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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