model_validate

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

No annotations exist, so the description carries the full burden. It does say issues are returned per field, but never states that this is a non-mutating/read-only check, what input format the model string takes, or what happens on a malformed payload.

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?

One compact sentence, front-loaded with the verb and resource, with the return shape appended. No filler, but also little substance.

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?

No output schema exists, so the description is the only source of return information and it provides just three words ('field-specific issues'). Combined with the undocumented input format, an agent cannot confidently construct a valid call.

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 single 'model' parameter has 0% schema description coverage, and the description only implies it is a whole /m:os model body. It does not clarify whether that string is JSON, a DSL, or reference a stored model, which is the key ambiguity for this tool.

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?

States a specific verb and resource ('Validate a complete /m:os model') and adds the outcome ('return field-specific issues'). It reads distinctly from siblings like model_create and model_get, though 'complete' is left unexplained.

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?

There is no statement of when to call this instead of model_create/model_update, no note on whether validation is a prerequisite before saving, and no exclusions. Usage is only weakly implied by the verb.

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