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bitscorp-mcp

MCP FFmpeg Video Processor

by bitscorp-mcp

extract-audio

Extract audio from video files in MP3, AAC, WAV, or OGG format using the MCP FFmpeg Video Processor. Convert video to audio by specifying input path and desired format.

Instructions

Extract audio from a video file

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoPathYesPath to the video file to extract audio from
formatNoAudio format to extractmp3
outputDirNoOptional directory to save the output file (defaults to a temporary directory)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't cover important behavioral aspects like whether it modifies the original video file, what permissions are needed, error handling, or performance characteristics. The description is minimal and lacks operational context.

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 with just one sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it front-loaded and efficient. Every word earns its place in conveying the core functionality.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., path to extracted audio file, success/failure indicators) or important behavioral details. For a tool that performs file operations with multiple parameters, more context is needed for effective use.

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 description doesn't add any parameter information beyond what's already in the schema, which has 100% coverage with clear descriptions for all parameters. The baseline score of 3 reflects that the schema adequately documents parameters, so the description doesn't need to compensate but also doesn't provide additional value.

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's purpose with a specific verb ('extract') and resource ('audio from a video file'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-video-info' or 'resize-video', which might also involve video processing but serve different functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or any context-specific usage scenarios, leaving the agent to infer based on tool names alone. There's no explicit when/when-not 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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