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Ableton Copilot

Ableton Copilot

by F-Fischer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_selected

Fetch the track, scene, and device currently selected in Ableton Live to provide precise context for your music production commands.

Instructions

Get the track, scene, and device currently selected in the Live UI.

Parameters:

  • user_prompt: The original user prompt that led to this tool call (for telemetry)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_selected"
  }
}

Input Schema

NameRequiredDescriptionDefault
user_promptNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not mention that the operation is read-only, what happens if nothing is selected, or any return format. The description is purely functional and lacks behavioral context.

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: a single sentence stating the purpose, followed by a minimal parameter explanation. No wasted words, and the structure clearly separates purpose from parameter 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?

The tool has no output schema, yet the description does not describe the return value structure or behavior in edge cases (e.g., nothing selected). It is minimally adequate for a simple getter but leaves out details an agent might need to use the result effectively.

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 only lists user_prompt with type and default, but the description adds: 'The original user prompt that led to this tool call (for telemetry).' This meaningfully clarifies that the parameter is for telemetry rather than functional use, compensating for the 0% schema description coverage.

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 the tool's function: 'Get the track, scene, and device currently selected in the Live UI.' This provides a specific verb and resource. It does not explicitly mention alternatives, but the 'currently selected' scope differentiates it from sibling tools like get_track_info.

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?

There is no guidance on when to use this tool versus alternatives, no mention of context, prerequisites, or when not to use it. The description only states what it does, without helping the agent decide when to invoke it.

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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