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mcp_opendaw_create_random_walk_melody

Generate a melody by walking up or down a scale stepwise, producing coherent yet unpredictable sequences. Adjust step size, direction bias, rests, and note durations.

Instructions

Create a melody using a random walk through a scale — stochastic generation.

Each note is chosen by walking up or down the scale from the previous note. The walk is constrained by max_step (how many scale degrees can move per step) and direction_bias (probability of ascending vs descending).

This produces melodies that feel coherent (smooth stepwise motion) yet unpredictable — the hallmark of generative music. Brian Eno's generative systems, Xenakis's stochastic pieces, ambient textures, IDM melodies.

Unlike generate_melody (contour-guided weighted random), random walk produces stepwise motion where each note depends on the previous one — creating the melodic continuity that contour guidance doesn't guarantee.

Args: root: Root note name (C, C#, D, ...). scale: Scale name (major, minor, dorian, phrygian, lydian, mixolydian, harmonic_minor, melodic_minor, pentatonic_major, pentatonic_minor, blues). bars: Number of bars (1-32). At default duration=0.5, 4 bars = 32 notes. octave: Starting MIDI octave (1-6, default 4 = C4=60). max_step: Maximum scale steps per move (1-7, default 3). 1 = only adjacent scale tones (very smooth, stepwise). 2 = allow skips of up to a third. 3 = up to a fourth (mix of steps and skips). 5 = up to a sixth (dramatic leaps). 7 = full octave (free movement). direction_bias: -1.0 to +1.0 (default 0 = equal up/down). Negative = tend downward, positive = tend upward. 0.5 = 75% chance up, 25% down. duration: Note duration in beats (0.0625-4.0, default 0.5 = eighth). duration_variation: "none" (uniform), "slight" (+/-50%), "wide" (16th to half), "dotted" (mix of dotted and straight). rest_probability: 0-0.5 (default 0 = no rests). Inserts rests instead of notes at the given probability. velocity: Base velocity 0-1. velocity_variation: "none" (uniform), "slight" (+/-0.1), "dynamic" (+/-0.3), "human" (gaussian-ish, +/-0.15). boundary_behavior: "reflect" (bounce back at octave limits), "wrap" (wrap around), "clamp" (stay at boundary). seed: PRNG seed for reproducibility. unit_index: AU index. track_index: Note track index. start_beat: Starting beat position.

Returns notes created, walk statistics (range, average interval, direction ratio), and seed for reproducibility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barsNo
rootNoC
seedNo
scaleNominor
octaveNo
durationNo
max_stepNo
velocityNo
start_beatNo
unit_indexNo
track_indexNo
direction_biasNo
rest_probabilityNo
boundary_behaviorNoreflect
duration_variationNonone
velocity_variationNonone

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses the stochastic algorithm: notes depend on previous ones, max_step constrains movement, direction_bias sets probability, and boundary behavior controls octave limits. It even mentions return statistics (range, average interval, direction ratio), giving a clear picture of the tool's behavior beyond its name and schema.

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 long but well-structured: a clear opening definition, algorithm explanation, artistic context, sibling comparison, and a systematically formatted Args list. Given 16 parameters, every section earns its place without redundancy or fluff.

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

Completeness5/5

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

Despite 16 parameters, zero schema descriptions, and no annotations, the description covers all parameters, provides defaults, ranges, relationships (e.g., bars vs duration), musical use cases, and return values. The output schema is noted as present, so not explaining exact return structure is acceptable. It is complete for a complex generative tool.

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 coverage is 0%, but the description documents every parameter with ranges, defaults, and examples. For instance, 'max_step: Maximum scale steps per move (1-7, default 3). 1 = only adjacent scale tones...' and 'direction_bias: -1.0 to +1.0... 0.5 = 75% chance up.' This fully compensates for the schema's lack of descriptions.

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 exactly what the tool does: 'Create a melody using a random walk through a scale — stochastic generation.' It uses a specific verb, resource, and method, and clearly distinguishes itself from the sibling generate_melody by contrasting stepwise dependence with contour-guided weighted random.

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

Usage Guidelines5/5

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

The description provides rich usage context, naming aesthetic applications (Eno, Xenakis, ambient textures, IDM melodies) and explicitly comparing to generate_melody: 'Unlike generate_melody (contour-guided weighted random), random walk produces stepwise motion where each note depends on the previous one.' This tells the agent when to choose this tool over an alternative.

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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