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mcp_opendaw_expand_intervals

Scale melodic intervals between notes to expand or compress a melody's contour, using an anchor note or center pivot. Optionally snap results to a scale.

Instructions

Expand or compress melodic intervals by a factor.

Multiplies the interval between each consecutive pair of notes by factor. Values >1 widen the melody (small steps become leaps), values <1 narrow it (leaps become steps). The first note's pitch is kept as anchor (or centered around the mean pitch).

This is a fundamental transformation in motivic development:

  • factor=2.0: seconds become thirds, thirds become fifths

  • factor=0.5: thirds become seconds, fifths become thirds

  • factor=1.5: gentle expansion, more expressive contour

Args: unit_index: Audio unit index track_index: Note track index region_index: Region index (-1 = first region) factor: Interval multiplier (0.25-4.0). 1.0=no change, 2.0=double all intervals, 0.5=halve all intervals. anchor: Anchor point — "first" = keep first note pitch, expand from there, "center" = keep mean pitch, expand symmetrically, "last" = keep last note pitch, expand backwards. snap_to_scale: Scale name for snapping results ("major", "minor", "dorian", "phrygian", "lydian", "mixolydian", "locrian", "harmonic_minor", "melodic_minor", "" = no snapping, chromatic result). root: Root note for scale snapping (C, C#, D, ... B).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNoC
anchorNofirst
factorNo
unit_indexYes
track_indexYes
region_indexNo
snap_to_scaleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explains the transformation algorithm in detail (interval multiplication, anchor handling, snapping) and parameter constraints. However, it does not disclose side effects like undo behavior or whether notes are modified in-place, though the mutating nature is inherent.

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 well-structured: a one-line summary, a short explanation with examples, and a parameter breakdown. Despite its length, every sentence adds value, and the most critical information is front-loaded.

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 complex transformation with 7 parameters, the description covers the core logic, anchoring, snapping, and concrete examples. It does not mention prerequisites (e.g., region must contain notes) or potential clipping/range limitations, but the output schema likely handles return value expectations.

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?

Schema description coverage is 0%, and the description fully compensates by explaining all 7 parameters, including defaults, constraints (factor 0.25-4.0), and the meaning of each anchor option and snapping scale. This goes well beyond the bare schema.

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 'Expand or compress melodic intervals by a factor' — a specific verb and resource — and elaborates on the mechanism. It does not explicitly reference sibling tools for differentiation, but the unique interval-multiplication behavior makes it distinct.

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 implies usage in motivic development ('This is a fundamental transformation in motivic development') and provides factor examples, but it does not explicitly state when to choose this tool over alternatives such as invert_notes or double_melody, nor does it mention any exclusions.

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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