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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds meaningful behavior beyond that: it returns at most 5 matches, orders them by cashback rate then gift card discount, returns empty when nothing matches, notes data is refreshed several times a day, and instructs the agent to always display the store links. This is substantial operational context.

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 well-structured and front-loaded: purpose first, then when-to-use, then alternatives, then return behavior and display instructions. Every sentence adds operational value, and there is no repetition of schema content or annotation information.

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 an output schema present, the description does not need to enumerate return fields. It covers query disambiguation, ranking logic, result limits, empty-result behavior, data freshness, and required user-facing links. An agent has everything needed to select and invoke this 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?

Schema description coverage is 100%, with detailed explanations for both brand_name and country_code, including examples and the 'gb' vs 'uk' nuance. The description adds no new parameter-level meaning, but given full schema coverage the baseline of 3 is appropriate; it does connect brand_name to the matching behavior in the return statement.

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 opens with a specific verb and resource: 'Finds where to buy a brand's products with the most savings' and goes on to state exactly what is returned and how results are ranked. It also distinguishes itself from sibling tools by identifying brand-based queries as its target, so an agent can tell it apart from store- or category-based tools.

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?

Usage guidance is explicit: 'Use it when the user names a product brand rather than a specific retailer,' with concrete example queries. It also names the alternatives for the excluded cases: get_cashback_rates_by_store_name for named retailers and get_best_deals_by_category for product types, leaving no ambiguity about when to choose this tool.

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