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waveform-MCP

waveform-MCP

by jarmstrong158
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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theory_arrangement_layers

Retrieve arrangement layers (foundation, harmonic_glue, lead, counter_melody, atmosphere, ear_candy) and optional per-section presence values to determine which layers should be active in a composition.

Instructions

Return arrangement layers: foundation, harmonic_glue, lead, counter_melody, atmosphere, ear_candy. Optional section returns per-section presence values for each layer (0..1) from LAYER_PRESENCE_BY_SECTION — drives the 'which layers should be active' decision.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "theory_arrangement_layers"
  }
}

Input Schema

NameRequiredDescriptionDefault
sectionNointro/verse/chorus/etc.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the read-only nature implicitly through 'Return' and mentions the LAYER_PRESENCE_BY_SECTION data source, but does not address error behavior or output format.

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 primary purpose. The optional parameter behavior is explained in the second sentence without unnecessary detail.

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

Completeness4/5

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

For a simple read-only tool with one optional parameter and no output schema, the description explains both invocation modes and the nature of the returned data. It doesn't specify exact output formatting or invalid-section behavior, but that is a minor gap.

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?

The schema describes section as 'intro/verse/chorus/etc.', and the description adds that it is optional, returns per-section presence values in 0..1, and drives the layer activity decision. This goes beyond the schema's basic type hint.

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?

Clearly states it returns arrangement layers and enumerates them. The optional section behavior is also described, distinguishing it from other theory tools that return chord/scale info.

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?

Explicitly states that optional section returns per-section presence values and connects it to the 'which layers should be active' decision, giving a concrete use case. It does not name an alternative sibling tool, but the usage context is sufficient for a simple query.

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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