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extao15

garageband-llm-bridge

by extao15

garageband_score_spec_schema

Retrieve the JSON score schema with supported pitch/drum names and timing rules to generate valid GarageBand scores.

Instructions

Return the LLM-friendly JSON score spec schema, examples, supported pitch/drum names, and timing rules.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns schema, examples, and rules, but does not explicitly state that it is a read-only, non-destructive operation. However, the behavior is safely inferred from the purpose.

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 a single sentence that precisely states the tool's output without any extraneous information. It is front-loaded and every word contributes to clarity.

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

Completeness5/5

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

Given the tool has no parameters, no output schema, and low complexity, the description fully covers the tool's purpose and expected return value. It is complete for an information-retrieval tool.

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?

The input schema has zero parameters, so by guidelines the baseline score is 4. The description adds no parameter details because none exist, which 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?

The description clearly states the tool returns an 'LLM-friendly JSON score spec schema, examples, supported pitch/drum names, and timing rules.' This specifies both the verb ('Return') and the resource (score spec schema), differentiating it from sibling tools like garageband_validate_score_spec which validates, or garageband_score_spec_to_midi which converts.

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 usage for obtaining the schema/metadata but provides no explicit guidance on when to use this tool versus alternatives like garageband_validate_score_spec or garageband_score_spec_to_midi. It lacks context for exclusion or recommended scenarios.

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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