model_report

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

With no annotations, the description must fully disclose behavior. It fails to state whether this is a read-only operation, whether it requires specific permissions or state, or what the 'honest verdict' entails (e.g., limitations, accuracy metrics, or caveats). The description only hints at content, not 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 a single concise sentence that front-loads the key purpose. Every word adds value, and there is no redundancy or unnecessary elaboration.

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 absence of an output schema, the description should clarify what the report contains. 'Backtest summary' is vague, and 'honest verdict' is ambiguous; it could describe performance metrics, model limitations, or a subjective assessment. The description is minimally adequate but leaves the agent uncertain about return format and scope.

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?

There are zero parameters, so the baseline is 4. The description doesn't need to explain parameter meanings, and it doesn't create any confusion. No additional parameter semantics are required.

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 states that the tool returns a backtest summary and a verdict from the last training run. It identifies the resource (model report) and the content, though it lacks an explicit verb like 'get' or 'retrieve.' It is distinct from sibling tools like data_status or query_warehouse.

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 guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites such as a completed training run, nor any indication of when a user might prefer this over other data tools.

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