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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), so the bar is lower. The description adds real behavioral context: results are 'normalized product cards' with 'live facet metadata', and facet filters must be sourced from a prior response, which is non-obvious stateful behavior.

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?

Three sentences, each earning its place: purpose first, return shape second, invocation constraint third. No filler and the most decision-relevant information is front-loaded.

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 a full output schema and 100% parameter coverage, the description need not explain return values, and it still summarizes them. It is complete enough to call correctly, with the only gap being sibling differentiation that lives outside this tool's own scope.

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 the schema already states that category and filter values come from prior facet metadata and that q/category are mutually required. The description mostly restates these constraints rather than adding new syntax or format detail, so the 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?

The description states a specific verb (Search) and resource (Boots UK products) plus a secondary mode (browse public product categories), which is more than a tautology. However, it never names or contrasts with the only sibling, boots_suggest, so an agent must infer the search-vs-suggest distinction on its own.

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?

"Supply q, category, or both" gives an explicit requirement, and "category values come from a prior category facet" tells the agent the correct workflow sequence. It stops short of when-not-to-use guidance or pointing to boots_suggest as the alternative for autocomplete-style lookups.

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