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

No annotations are provided, so the description bears the full disclosure burden. It is useful that it enumerates response contents (training steps, quality scores, recommended flag) in the absence of an output schema, but it omits pagination behavior, permission requirements, and any hint that versions can be soft-deleted even though an include_deleted parameter exists.

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 zero filler; the resource and the payoff (which fields you get back) come first. Nothing is redundant with structured fields.

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 simple two-parameter read tool with full schema coverage, the description covers purpose and return contents adequately. The only real gap is sibling routing guidance and the fact that deleted versions are excluded by default, which the schema already states.

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 description coverage is 100%, so both model_hash (SHA-1 pattern) and include_deleted (default false) are already fully documented in the schema. The description adds no extra meaning about either parameter, so baseline 3 applies.

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 ('Get version history for a model') and enumerates the returned data points (training steps, quality scores, recommended flag). This clearly separates it from siblings like GetModelDetails and GetAssetModels, though it never explicitly names the boundary between them.

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 statement of when to use this tool versus GetModelDetails or GetAssetModels, and no prerequisites or conditions given. Usage is only inferable from the name, which is weak guidance for a tool with two parameters.

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