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

Annotations already mark it read-only and idempotent, and the description adds real behavioral detail: it returns per-week prices, first/last values, absolute and percentage change, and high/low weeks, and cites the European Commission Weekly Oil Bulletin with availability back to 2005. No contradiction 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 core purpose and return contents are front-loaded in the first sentence, with illustrative questions and source details following. It is slightly longer than strictly necessary but every sentence contributes useful context.

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?

Even without an output schema, the description spells out what the response includes and gives the data source and historical depth. It does not mention error conditions or lack-of-coverage cases, but sibling tools like fuel_price_coverage can cover those gaps.

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 schema already documents country, fuel, weeks, and since. The description's examples reinforce valid fuel values and the notion of weekly windows, but it does not add major parameter semantics 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?

The description states the tool returns a weekly series of pump prices for one European country over time, with the price change over the period. It is clearly distinguished from siblings like compare_fuel_prices and fuel_price by emphasizing single-country history and trend questions.

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?

Concrete example questions ('how much has petrol gone up in Germany this year', 'diesel price trend in France') make the intended use explicit. It does not explicitly name alternatives or when-not-to-use cases, so it stops short of a 5.

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