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store_rack_macro_variation

Plan or store a native variation of mapped rack macros, binding exact rack and parameter state and reporting Live's observed count for confirmation.

Instructions

Plan or store a new native variation of mapped rack macros. Binds exact rack and parameter state and reports Live's observed count; variation contents are not exposed by Live's API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNoOmit or true to return a plan; false requires a valid confirmationToken.
trackIdYesStable device-owner ID: track-N from list_tracks, return-N from get_set_mixer, or master.
deviceIdYesStable device ID returned by list_devices.
planHashNoHash returned by the matching dry run.
confirmationTokenNoShort-lived, single-use token returned by the matching dry run.
expectedStateVersionYesExact stateVersion observed immediately before planning.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, and openWorldHint=true. The description adds genuinely new behavioral context: it binds exact rack and parameter state, and crucially warns that variation contents are not exposed by Live's API, which prevents an agent from attempting to read back what it stored. It omits the confirmation-token/single-use semantics, but those live in the schema.

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?

Two sentences, both front-loaded with the operation and its key limitation, with no filler. The API-limitation caveat is placed where it will be read before invocation.

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?

No output schema exists, and the description usefully notes that the tool reports Live's observed count and cannot expose variation contents, which covers the return-value gap. What remains thin is the plan-then-confirm sequencing, though that is fully documented in the parameter descriptions.

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?

Schema description coverage is 100%, so the schema already explains dryRun, expectedStateVersion, planHash, and confirmationToken. The description's 'binds exact rack and parameter state' loosely gestures at expectedStateVersion but adds no syntax, format, or ordering detail beyond the schema. Baseline 3 is correct.

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?

States a specific verb pair (plan or store) plus a precise resource (a new native variation of mapped rack macros), which cleanly separates it from siblings like recall_rack_macro_variation, delete_rack_macro_variation, and map_rack_macro_to_parameter. An agent can identify the operation without opening the schema.

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?

'Plan or store' implies the two-phase dry-run/commit workflow, but the description never states when to choose this tool over its recall/delete siblings or when the store path is appropriate. Usage is implied rather than stated, leaving the agent to infer conditions from the schema.

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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