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

Annotations already establish read-only, idempotent, closed-world behavior, so the description's job is interpretive context — and it delivers: posted shelf prices rather than prices paid, no product names, index levels are not price levels, and matched/matchedShare indicate the sample size behind each row. These are exactly the caveats an agent needs to avoid misreporting results, though rate limits or response shape are not discussed (output schema covers the latter).

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, followed by disclaimers and then the vintage routing rule; every sentence carries information. It is dense with caveats, but none are redundant, and no sentence merely restates the title.

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 five-parameter read tool with full schema coverage, an output schema, and complete annotations, the description supplies the remaining interpretive layer: scope (UK/AU, posted online shelf prices), limits (no product names, not a price-level or CPI measure), and vintage routing. Nothing an agent needs in order to call and interpret it 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% and each parameter (class, market, vintage, retailer, recordType) is documented with examples and enums in the schema itself. The description adds no new parameter-level meaning — its 'omit vintage for the latest week' note is already in the schema — so baseline 3 applies.

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 and resource ('Returns one published week of the UK or Australian online shelf-price index') and enumerates the payload: index levels, week-on-week change, and matched-product counts by retailer and product class. It also draws hard boundaries against confusable concepts (CPI, government statistic, price levels), so an agent can tell it apart from siblings like lookup_basket_prices.

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 routing rule: 'Omit vintage for the latest week; list_index_vintages gives the others,' which names the alternative and the condition that selects it. It does not cover when to prefer about_the_data or lookup_basket_prices instead, so the guidance is clear but not exhaustive.

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