garageband_validate_score_spec

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

No annotations are provided, so the description must fully disclose behavior. It only says 'Validate' without specifying read-only nature, side effects, or output (e.g., returns success/failure or errors). The lack of detail on validation outcomes or state impact is a significant gap.

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

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

The single-sentence description is concise and front-loaded with the action 'Validate'. Every word contributes to the purpose, with no redundancy.

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

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

Given the tool's complexity (validating a spec with a nested object parameter), the description lacks crucial details: what defines validity, error reporting, return format, and potential prerequisites (e.g., referencing garageband_score_spec_schema). Without output schema or further guidance, an agent cannot correctly use this tool.

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

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

Schema description coverage is 0%, and the description does not elaborate on the 'score_spec' parameter beyond its name. It doesn't specify required fields, format, or examples, which is essential for a complex object parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates an LLM-friendly JSON band score spec, with a specific purpose: before MIDI generation or opening GarageBand. It distinguishes from siblings like garageband_score_spec_to_midi (which uses the spec) and garageband_score_spec_schema (which returns the schema).

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

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

The description gives a clear usage context ('before generating MIDI or opening GarageBand'), implying it's a validation step. It doesn't explicitly state when not to use it or name alternatives, but the context is sufficient for appropriate tool selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.