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waveform-MCP

waveform-MCP

by jarmstrong158
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

audio_spectrum

Analyze audio frequency balance by returning RMS energy per band, enabling comparison to a reference mix to spot tonal differences.

Instructions

Return RMS energy per frequency band. bands defaults to a 10-band log-spaced layout (sub, low, low-mid, mid, hi-mid, presence, brilliance, air). Useful for 'compared to my reference, this song is 4 dB heavier in the low-mid region.'

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_path": "<file_path>"
    },
    "name": "audio_spectrum"
  }
}

Input Schema

NameRequiredDescriptionDefault
bandsNo
file_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the default band count and log-spaced layout, but doesn't specify output format, units, or whether the entire file is analyzed. The example mentions dB, which could create ambiguity against 'RMS energy' without clarification.

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?

Two sentences, front-loaded with the core function, followed by a concrete use-case example. Every sentence earns its place with no redundancy.

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?

The tool is simple and the description covers the main purpose and band defaults. However, with no output schema, the lack of explicit return-format or units is a gap, and the dB example introduces some ambiguity. It's mostly adequate but not fully complete.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains the bands parameter's default value and layout, and file_path is self-explanatory. For a two-parameter tool, this is reasonable compensation.

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 states a specific verb ('Return') and resource ('RMS energy per frequency band'), clearly distinguishing it from sibling analysis tools like audio_detect_tempo or audio_compare. The example use case reinforces its spectral-analysis purpose.

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 'Useful for...' sentence gives a concrete scenario (comparing frequency balance to a reference), which clearly implies when to use this tool. It doesn't explicitly name alternatives or exclusions, so it stops short of full routing guidance.

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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