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bschoepke

ableton-live-mcp

by bschoepke

live_exec

Execute Python statements inside Ableton Live to query or modify the session, tracks, clips, and devices through bindings for song, app, and Live objects.

Instructions

Execute Python statements inside Live with song, app, obj, this, Live, and result bindings. Set result to a compact dict/list summary to return it. General Live object-model bridge; examples are heuristics, not limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
refNo
detailNo
max_itemsNo
max_depthNo
max_string_lengthNo
timeoutNoSeconds to wait for Live's main thread.
expected_set_signatureNo
Behavior2/5

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

With no annotations, the description should disclose behavioral traits. It mentions result binding but not side effects, destructive potential, or required permissions, leaving the agent unaware of risks.

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 brief with two sentences. The first sentence front-loads the core purpose, but the second sentence is somewhat vague. Space is used efficiently.

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

Completeness2/5

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

Given 8 parameters, no output schema, and nested objects, the description is insufficient. It does not explain how to use ref or control output with detail/max_items, making it incomplete for safe agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 13% (only timeout described). The description does not explain most parameters (code, ref, detail, max_items, etc.), failing to add meaning beyond the schema.

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 executes Python statements with specific bindings, but does not differentiate from sibling live_eval, leaving ambiguity about when to use which.

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?

No explicit guidance on when to use this tool versus alternatives like live_eval. The statement 'examples are heuristics, not limits' is vague and does not provide clear usage context.

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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