validate_model

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

With no annotations, the description carries the behavioral burden. It discloses an important behavioral trait: spelling suite violations are placed in a separate 'spelling' array and excluded from the 'violations' count, so the gate reflects only structural/semantic issues. This is meaningful beyond what a generic 'validate' label would convey, though it does not explicitly state read-only/side-effect behavior.

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 description is compact and front-loaded: the first sentence states the action and result, and the second sentence adds a precise behavioral detail about spelling violations. Every sentence earns its place with no redundant filler.

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?

For a zero-parameter tool with an output schema, the description is complete: it explains what the tool does, the key distinction between 'spelling' and 'violations', and the purpose of the 0-errors gate. No additional context is needed to call it correctly.

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?

The input schema has zero parameters and schema description coverage is 100%, so there are no parameter semantics to document. The baseline for a zero-parameter tool is 4, and the description appropriately spends no space on parameters.

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 states a specific verb ('Run') and resource ('built-in model validation') and clearly identifies the return artifact ('structural violations'). It also differentiates this from sibling check/reporting tools by focusing on model validation rather than coverage, naming, or metrics.

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 useful context about a '0-errors gate' and implies this tool is the validation entry point, but it does not explicitly say when to use it versus siblings like check_requirement_coverage, check_documentation_coverage, or check_naming_conventions. The usage context is implied rather than stated.

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