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export_vocal_midi

Exports a melody and lyrics as a MIDI file for singing synths, placing syllables on notes at the song's tempo; reports installed singers and loading steps.

Instructions

For a real singing voice: writes a melody item and its lyrics as a MIDI file that singing synths (Synthesizer V, ACE Studio, VOCALOID, OpenUtau) import with the words on the notes, at the song's tempo and positions. Says which singers are installed and how to load it. The singer renders the vocal; then insert_audio_file it at bar 1 (the file starts at the song's start) and mix it like any vocal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
holdNoThe singer's melisma mark: '-' (Synthesizer V, ACE Studio, VOCALOID) or '+' (OpenUtau)-
nameNoFile and part nameLead Vocal
lyricsYesOne syllable per note: 'dan-cing in the dark _' (hyphens split syllables, '_' holds)
item_idYesMIDI item id from create_midi_item/get_track_details, or "selected"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.19.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses useful behavior: the file starts at the song's start, output goes at bar 1, tempo and positions are baked in. But it doesn't state whether the export mutates the project, what permissions are needed, or whether the file is written to disk vs returned (no output schema), leaving a real behavioral gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, but the first sentence is a long run-on that mixes purpose, consumers, and output semantics. The workflow guidance is useful but not tightly front-loaded. Some redundancy between 'writes a melody item' and the export framing.

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?

For a 4-param export tool with no annotations and no output schema, the description covers purpose, workflow, and downstream consumption well. It omits the return shape (does it return a file path? a status?) which matters when no output schema exists, keeping it from a 5.

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 coverage is 100%, so the schema already documents all four parameters including the melody mark and lyric syntax. The description adds almost no parameter detail beyond what the schema provides, so baseline 3 is appropriate.

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 (writes/exports) and resource (melody item + lyrics as MIDI file) and directly names the downstream consumer class (singing synths). Distinguished from siblings like write_melody or export_mix by its vocal-MIDI target.

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?

Description explains the workflow context (export the MIDI, then render the vocal with the singer, then insert_audio_file at bar 1, then mix). That is strong when-to-use guidance for the follow-up steps. However it does not explicitly name when NOT to use it versus alternatives like add_robot_vocal or write_melody.

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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