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

The annotations already declare the tool as readOnly and non-destructive. The description adds valuable context about the return structure (driver_standings, constructor_standings, meta.source) which helps the agent understand what to expect. It also clarifies that 'current points and position are the answer' to championship questions, a subtle but useful behavioral note. No contradictions with annotations.

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 succinct and well-structured. It front-loads the core purpose in the first sentence, then adds quick clarifications about usage and exclusions. The Args/Returns sections are organized and only include necessary information. No wasted words.

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?

The tool is simple with one parameter, rich annotations (readOnly, openWorld, idempotent), and an output schema. The description covers the equivalent of the output schema's fields (driver/constructor standings) and meta.source, so no critical information is missing. It fully equips an agent to call the tool correctly.

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 schema covers 100% of the parameter (year) with a description and example. The description repeats the year parameter in Args, adding no new information beyond the schema. The schema already provides the necessary semantics, so the description does not need to add more; 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 verb 'Return' and the resource 'F1 driver and constructor championship standings for a year'. It distinguishes this tool from siblings by specifying it's for championship standings, not race results or lap times. The use case example ('who is leading / who will win') further clarifies the purpose.

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 provides a clear context for usage: when asking about F1 championship standings. It also explicitly excludes other sports ('This is not a cricket or football tool'), which helps avoid misuse. However, it does not explicitly name alternatives like f1_get_race_results or when to prefer them, though the domain (F1) and resource (standings) make the distinction relatively clear.

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