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get_looper_performance_context

Read-only

Fetch a snapshot of a Looper device's current state, including quantization, monitor, song/tempo control, exposed parameters, routing, and transport. Use it to inspect performance context before making changes.

Instructions

Read one native snapshot of a loaded Looper's State, Quantization, Monitor, Song Control, Tempo Control, all exposed parameters, global clip-launch quantization, track input/output routing, monitoring, and transport. Read-only; source readiness and audible outcome are not inferred.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trackIdYesStable device-owner ID: track-N from list_tracks, return-N from get_set_mixer, or master.
deviceIdYesStable device ID returned by list_devices.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds the caveat that source readiness and audible outcome are not inferred, which is a behavioral disclosure beyond the annotations. This clarifies interpretation of the snapshot without contradicting the annotations.

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 a single dense sentence that front-loads the core action ('Read one native snapshot') before listing the detailed components. It is efficient and contains no fluff, though the long list could be slightly more structured, it remains readable and purposeful.

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 description enumerates many fields that are read but does not describe the output structure, error conditions, or prerequisites beyond the implicit requirement of a loaded Looper. Given there is no output schema, this leaves some ambiguity about the return format, but for a read tool the listed scope is reasonably complete.

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

Parameters3/5

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

The input schema already provides 100% coverage with clear descriptions for both trackId and deviceId. The description adds no parameter-specific details beyond what the schema states, so it earns the baseline score of 3 for a fully documented 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 reads a snapshot of a Looper's performance context and enumerates the exact components (State, Quantization, Monitor, etc.). It distinguishes itself from write tools like set_looper_state and from other read tools like get_transport_context by focusing specifically on the Looper's full context.

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

Usage Guidelines3/5

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

The description implies read-only usage and adds a caveat that source readiness and audible outcome are not inferred, which hints at when not to use it. However, it does not explicitly name alternatives or conditions for choosing this over similar read tools like get_beat_repeat_performance_context or get_transport_context. Guidance is present but not explicit.

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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