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mcp_opendaw_add_automation

Add parameter automation to an audio effect by creating automation tracks and value clips based on time-position pairs.

Instructions

Add parameter automation to an effect on an audio unit.

Creates an automation track + value clip + value events. Automation points control the parameter over time.

unit_index: Audio unit index. effect_index: Effect position in the chain. parameter_name: Parameter to automate (e.g. "cutoff", "volume", "mix"). points: JSON array of [position_beats, value_0_to_1] pairs. Example: "[[0, 0.5], [4, 1.0], [8, 0.5]]"

The parameter must be automatable (Field<Pointers.Automation>).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointsYes
unit_indexYes
effect_indexYes
parameter_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description explains the tool creates an automation track, value clip, and value events, and specifies that the parameter must be automatable. However, with no annotations, it misses details on error handling, side effects like overwriting existing automation, and the return value structure.

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 concise and front-loaded with the purpose. It efficiently covers the key information in a few sentences without unnecessary details.

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?

Given the moderate complexity (4 required params, no nested objects, output schema exists), the description covers the core functionality and parameter semantics. However, it lacks information on error conditions, prerequisites, and what the output schema returns, making it only partially 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?

The input schema has 0% description coverage, and the description compensates by explaining each parameter: unit_index, effect_index, parameter_name with examples, and points with format and example. The descriptions are clear and add value beyond the empty schema.

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 clearly states the tool adds parameter automation to an effect on an audio unit, with specific verbs and resources. It distinguishes from sibling tools like add_instrument_automation by specifying 'effect on an audio unit'.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites like checking automatable fields with list_automatable_fields, nor does it indicate when to use add_instrument_automation instead.

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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