validate_model

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds the specific validation checks (missing nodes/elements/materials, overlaps), which is useful, but it does not disclose what happens after validation, such as return values, errors, or whether issues block analysis. This is a moderate contribution beyond annotations, not a rich one.

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 with the core purpose, followed by a clear bulleted list. The bilingual repetition adds some redundancy but does not materially hurt usability, and no unnecessary filler is present.

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, the description covers what the tool checks and when to call it. However, since no output schema exists, the lack of any statement about what the tool returns or how it signals discovered issues leaves an agent with some uncertainty about the tool's post-validation behavior.

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 tool has zero parameters, so there is nothing for the description to explain. The default baseline of 4 applies because no parameter semantic burden exists.

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 ('validate'), a resource ('the current model'), and the precise scope ('for common issues before running analysis'). It also enumerates the exact checks performed, which makes the tool's function unambiguous and easily distinguishable from related tools like run_analysis.

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 phrase 'before running analysis' gives clear temporal guidance on when to invoke this tool. It does not explicitly name alternatives or state when not to use it, but the context is sufficient for an agent to place it in the workflow.

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