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mabh111111

FFmpeg Python MCP Server

by mabh111111

convert_video_with_qsv

Convert video files using Intel QSV hardware acceleration for improved performance. Supports multiple output formats, encoders, and quality presets.

Instructions

使用Intel QSV硬件加速转换视频

Args:
    input_path: 输入视频文件路径
    output_path: 输出视频文件路径(可选)
    output_format: 输出格式(mp4, mkv, avi等)
    qsv_encoder: QSV编码器(h264_qsv, hevc_qsv, av1_qsv等)
    quality: 质量设置(high, medium, low)
    qsv_preset: QSV预设(veryfast, faster, fast, medium, slow, slower, veryslow)

Returns:
    转换结果信息

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_pathYes
output_pathNo
output_formatNomp4
qsv_encoderNoh264_qsv
qualityNomedium
qsv_presetNomedium
Behavior2/5

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

No annotations are provided, and the description lacks behavioral details such as whether the operation is destructive, what happens when output_path is null, rate limits, or permissions required. The description focuses on parameters but does not disclose the tool's side effects or return value structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, covering purpose and parameters in a single block with Args/Returns sections. It is front-loaded with the core purpose. No extraneous text. Slight improvement could be made by structuring parameter descriptions as a list for readability.

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?

For a 6-parameter tool with no output schema and no annotations, the description adequately explains parameter usage but lacks return value format details, error handling, hardware prerequisites, and behavioral context. Given complexity, it is partially complete but missing important contextual elements.

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?

The schema has 0% description coverage, so the description must compensate fully. It provides Chinese explanations for each parameter, including acceptable values for output_format, qsv_encoder, quality, and qsv_preset. This adds significant meaning beyond the bare schema types and defaults.

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 explicitly states '使用Intel QSV硬件加速转换视频' (Convert video using Intel QSV hardware acceleration), which is a specific verb+resource with technology identifier. It clearly distinguishes from siblings like convert_video_format (no QSV) and compress_video_with_qsv (compression instead of conversion).

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 mentions QSV hardware acceleration, implying it should be used when that acceleration is desired, but it does not explicitly state when to use this tool versus alternatives like convert_video_format or compress_video_with_qsv. No when-not-to-use or prerequisite conditions are provided.

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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