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export_parts

Splits a MuseScore score into individual instrument part files for easy sharing or rehearsal preparation.

Instructions

Export each instrument part from a score as a separate file.

First converts to MusicXML to discover part names and count, then uses MuseScore's JSON job format to export each part by index.

Args: score_b64: Base64-encoded score file. input_suffix: Input extension, e.g. "mscz". output_format: Format for each part output (pdf, musicxml, png, etc.).

Returns: List of {"part_index": int, "part_name": str, "format": str, "data": ...}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
score_b64Yes
input_suffixYes
output_formatNopdf

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the process (converts to MusicXML first, uses JSON job format), the return format (list of dicts), and that it discovers part names and counts. It does not address authorization or rate limits but adequately describes behavior.

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 brief purpose summary, a short technical overview, and a structured Args section. No wasted sentences or redundancy.

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?

Given the presence of an output schema, the description does not need to detail return values but does anyway. It covers the internal process, but lacks error handling, supported formats, or size constraints. Overall, it provides sufficient context for an AI agent.

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?

Schema coverage is 0%, but the description's Args section explains each parameter: score_b64 is base64-encoded score, input_suffix is the input extension, output_format is format with default pdf. This adds significant meaning beyond the bare 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 states a specific action ('Export each instrument part from a score as a separate file') clearly identifying the resource (instrument parts from a score) and the operation (export). It distinguishes from sibling tools like 'export_png_pages' and 'convert_score'.

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 when to use this tool (to export parts) but does not explicitly state when not to use it or suggest alternatives. No direct comparison to sibling tools like 'export_png_pages' or 'convert_score'.

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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