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

With no annotations, the description carries the full behavioral burden. It discloses that numbers are frozen at selection time, that the output includes a fit ladder and report with caveats, and that issue is null until first publication. It does not mention errors or authentication, but for a read-only retrieval tool, this is sufficient transparent 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 concise and front-loaded, starting with the purpose and rule, then covering the parameter and null behavior. The run-on first sentence is dense but information-rich. Overall, every sentence earns its place with minimal 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?

For a simple tool with one optional parameter and no output schema, the description covers the return content (fit ladder, report, caveats), the selection rule, and the null edge case. It lacks explicit info about error handling or response format, but these are minor gaps for this kind of tool.

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 coverage is 100% and the parameter description already includes the format, example, and default behavior. The tool description reiterates the parameter usage (pass week for past issue) but adds no new semantic detail beyond what the schema already provides. Baseline 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 states the tool returns the pick of the week, a specific model chosen by a published rule, along with fit ladder and report. It distinguishes itself from siblings (find_fit, gpu_prices, etc.) by naming the unique selection rule and the specific resource, making its purpose unambiguous.

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 implies usage for retrieving the weekly pick and explains the parameter for past issues, but it does not explicitly contrast it with sibling tools or state when not to use it. There is no mention of alternatives like gpu_prices or find_fit. The context is clear, but the guidance is not explicit.

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