music_plan_changes

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

The description adds useful behavioral traits (10-minute, single-use token; validation rather than application), but annotations are all false and unhelpful. It does not disclose whether the plan is persisted, if validation is a dry run, or other side effects.

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?

A single, front-loaded sentence with no filler. It conveys the core purpose and token details efficiently.

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?

Despite a complex schema and a workflow evident from siblings, the description does not explain how to construct operations, the validation process, or how the token relates to apply_changes. The context is insufficient for an agent to use this tool correctly without additional inference.

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 coverage is 0%, so the description must compensate. It only vaguely references 'library mutations' while the actual parameter is 'operations' with a complex discriminated union. The description adds minimal meaning beyond the schema.

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 a specific verb ('Validate') and resource ('library mutations'), and distinguishes itself from sibling tools like apply_changes, get_change_plan, and cancel_change_plan by focusing on validation and token issuance.

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?

No explicit guidance on when to use this tool versus alternatives. It implies a validation step before applying changes, but does not mention the workflow with siblings, prerequisites, or exclusions.

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