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199-mcp
by 199-mcp

isolate_audio

Extract clear voice from noisy audio recordings by removing background noise. This tool processes audio files to isolate speech for improved clarity.

Instructions

Removes background noise from audio. Returns: cleaned audio file path. Use when: extracting voice from noisy recordings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_file_pathYes
output_directoryNo
Behavior3/5

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 mentions the return value ('Returns: cleaned audio file path') which is helpful, but doesn't address important behavioral aspects like processing time, file format requirements, error conditions, or whether the operation modifies the original file. The description adds some value but leaves significant gaps.

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 two sentences that each serve distinct purposes: stating the core functionality and providing usage guidance. There's zero wasted language, and the information is front-loaded effectively.

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?

For an audio processing tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It explains the purpose and when to use it but lacks critical details about parameters, file requirements, processing behavior, and error handling that would be needed for reliable tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 2 parameters, the description provides no information about what 'input_file_path' or 'output_directory' mean, their expected formats, or constraints. The schema alone shows basic types but no semantic context, and the description fails to compensate for this significant gap.

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 the specific action ('Removes background noise from audio') and the resource being acted upon ('audio'), with a distinct purpose from sibling tools like 'enhance_dialogue' or 'speech_to_text' that focus on different audio processing tasks.

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

Usage Guidelines4/5

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

The description provides explicit usage context with 'Use when: extracting voice from noisy recordings', which clearly indicates when to apply this tool. However, it doesn't specify when NOT to use it or mention alternatives among the many sibling audio processing tools.

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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