validate_model

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

Beyond the readOnlyHint and idempotentHint annotations, the description details what exactly is checked (field types, ranges, enums, reference integrity) and crucially states what is NOT checked (runtime faults, convergence issues). This provides comprehensive behavioral transparency.

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 well-organized with a clear title, bullet-point list of checks, important caveats, and structured sections for preconditions, side effects, and next steps. Every sentence adds value without 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 complexity of the tool, the presence of an output schema, and the annotations, the description covers all necessary aspects: purpose, usage, behavioral details, parameter implications, and integration with other tools. It leaves no significant gaps.

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 100% coverage with clear descriptions for both parameters. The description adds no additional meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 identifies the tool as a 'Schema-based pre-flight check' and specifies its role after model modifications. It effectively distinguishes it from sibling tools like check_model_integrity and run_simulation by noting their different purposes.

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 explicitly states when to use it ('run after any model modifications') and provides preconditions (model loaded), side effects (none), and next steps (check_model_integrity, run_simulation). It also clarifies what it does not cover (EnergyPlus runtime faults), giving clear guidance on when not to rely solely on this tool.

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