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mcp_opendaw_automation_sweep

Create automation sweeps between two values over a beat range. Interpolates values for filter sweeps, fades, and pitch drops, auto-creating the automation track.

Instructions

Create a smooth automation sweep (ramp) between two values over a beat range.

Generates multiple automation events with interpolated values, creating smooth parameter transitions (filter sweeps, volume fades, pitch drops, etc.) in one call. Automatically creates the automation track if it doesn't exist yet.

unit_index: AU index. parameter_name: Instrument parameter to automate (e.g. "cutoff", "volume", "resonance"). start_beat: Start position in beats. end_beat: End position in beats. start_value: Starting normalized value (0.0-1.0). end_value: Ending normalized value (0.0-1.0). steps: Number of interpolation points (default 16, more = smoother). curve: "linear" (even spacing), "exp" (exponential, good for filter sweeps), "log" (logarithmic).

Returns the number of events created and a preview of the first few points.

Example: Filter sweep from closed (0.1) to open (0.9) over 16 beats: automation_sweep(unit_index=0, parameter_name="cutoff", start_beat=0, end_beat=16, start_value=0.1, end_value=0.9, steps=32, curve="exp")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
curveNolinear
stepsNo
end_beatYes
end_valueYes
start_beatYes
unit_indexYes
start_valueYes
parameter_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations exist, so the description carries the full burden. It discloses a key side effect: 'Automatically creates the automation track if it doesn't exist yet.' It also explains it generates multiple events and returns a preview. However, it does not mention whether existing automation events are overwritten, whether the operation is reversible, or any error conditions, which is significant for a write tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized with an overview, parameter list, return note, and example. Every section is useful, though it is somewhat long. The parameter list is necessary given the 0% schema coverage, and the example is valuable. Minor redundancy: the first sentence and the later transition mention overlap.

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?

The description covers purpose, full parameter semantics, return value, and a notable side effect (track creation). It is complete enough for an 8-parameter tool with no annotations. It lacks explicit error handling or edge-case info (e.g., what if start_beat > end_beat), but the provided details are strong.

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?

The input schema has zero descriptions (coverage 0%), so the description must compensate. It does so thoroughly: every parameter is documented with units (beats, normalized values 0.0-1.0), defaults (steps=16, curve='linear'), curve options with guidance ('exp' for filter sweeps), and an example that ties them together. This exceeds the baseline needed.

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 opens with a clear verb+resource+scope: 'Create a smooth automation sweep (ramp) between two values over a beat range.' It further explains the mechanism (generates interpolated events) and gives concrete examples (filter sweeps, volume fades), distinguishing this general-purpose tool from more specific siblings like create_filter_sweep or create_volume_fade.

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 states context—'creating smooth parameter transitions'—and lists typical use cases (filter sweeps, volume fades, pitch drops). It does not explicitly name alternatives or exclusions, but the use cases make it clear when this tool is appropriate. Lacks explicit 'use this instead of X' 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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