Skip to main content
Glama

set_device_parameter

Set a single device parameter in Ableton Live to modify a sound's tone. Specify the parameter by index or name, then provide a value or normalized fraction to apply the change.

Instructions

Set one device parameter — this is how you change a sound's tone.

- parameter: the parameter index (int) OR its exact name (str, case-insensitive).
- value: native units. For a continuous param a float in [min, max]
  (e.g. a frequency/dB/ms). For a quantized param, either an integer index
  into value_items or the exact value_items label string (e.g. "Lowpass").
- value_normalized: alternative to value, a 0.0-1.0 fraction mapped to
  min + x*(max-min); for quantized params it picks the value_items index.

Provide exactly one of value / value_normalized. The reply reports the
resulting display_value and whether the write applied (a parameter driven
by a macro is not writable).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trackNo
valueNo
parameterYes
track_indexYes
device_indexYes
value_normalizedNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It explains the write operation, the two value-input alternatives (value and value_normalized), the exact mapping formula for normalized values, and the important caveat that a macro-driven parameter is not writable. It also discloses that the reply includes display_value and whether the write applied, adding significant transparency beyond a bare 'Set parameter'.

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 and front-loaded with the main purpose. Each sentence adds value: the parameter identification method, value formats with examples, normalized alternative, exclusivity constraint, and response behavior. It is thorough without being verbose, and every line earns its place.

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?

Given the tool's complexity (six parameters, no annotations) the description covers most essential aspects: parameter addressing, value semantics, constraints, and return info. The output schema exists, so return values need not be detailed, but the description goes further by describing the reply. The only significant omission is the track/device selection parameters, which are not explained but are likely inferable from their names. Overall, it is nearly 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 schema has 0% description coverage, so the description must compensate. It thoroughly explains the complex parameters: parameter (index or exact name), value (native units with examples for continuous and quantized), and value_normalized (0-1 mapping formula). However, it does not describe track_index, device_index, or track, which are required or relevant parameters, leaving a gap in addressing the target device.

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 specific verb-resource pair ('Set one device parameter') and immediately clarifies its purpose ('this is how you change a sound's tone'), distinguishing it from sibling tools like set_device_enabled or set_macro. It is clear and unambiguous.

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 phrase 'this is how you change a sound's tone' provides clear context for when to use the tool, and the presence of sibling tools like set_macro and set_device_enabled implicitly differentiates it. However, it does not explicitly state when not to use it or name alternative tools, so it falls short of full explicit guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/verove-jordan/ableton12-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server