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

Annotations already declare readOnly/idempotent/openWorld, so the bar is lower, but the description still adds real behavior: results are capped at up to 5 engine/transmission/drivetrain variants (each with its own MPG), data is proxied live from fueleconomy.gov, and failures are explicit errors rather than empty successes, sometimes with valid options listed. It stops short of documenting rate limits or response shape details beyond the field list.

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?

Front-loaded with what the tool returns, then formatting guidance, then variant/error behavior — every sentence carries information. It is on the dense side and the parenthetical field list plus the long error sentence make it slightly heavier than needed, but nothing is filler.

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?

With no output schema and only three required params, the description covers return contents, the variant multiplicity that would otherwise surprise an agent, and the failure mode. Nothing an agent needs to call this correctly is missing.

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 the baseline is 3; the description adds value by stressing that the model string must match fueleconomy.gov verbatim and by giving concrete string variants ('Camry', 'F-150 2WD', 'Model 3'). It reinforces rather than duplicates the schema's cross-reference to fuel_economy_models, and adds no meaning for year or make beyond the schema.

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+resource (EPA fuel-economy ratings for a year+make+model), names the exact fields returned (city/highway/combined MPG, CO2, fuel type) and the data source. It also explicitly distinguishes itself from the sibling fuel_economy_models, which is the lookup helper rather than the ratings tool.

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?

Gives an explicit when-to-call-the-other-tool rule: 'if unsure, call fuel_economy_models first to see valid model strings for that year+make.' It also tells the agent how to format the model argument and what happens on unknown inputs, so no usage decision is left to inference.

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