boots_search

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

The description discloses that it 'returns one page' and includes product cards and live facets, which is useful behavioral context. With no annotations provided, the description carries the full burden. It does not explicitly state that the operation is read-only or mention any side effects, but for a search tool this is implicitly safe. It could be improved by explicitly stating it only reads public data.

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 concise at three sentences, front-loads the primary purpose and return type, and packs essential usage patterns without redundancy. Every sentence contributes meaningful information, making it efficient and well-structured.

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 tool with 9 parameters and no output schema, the description covers the main usage scenarios: querying by q, category, filters, sort, and price/stock controls. It mentions pagination indirectly ('returns one page') and explains dynamic facets, which are non-obvious. It doesn't delve into error handling or edge cases, but overall it is sufficiently complete for an agent to call it 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?

Input schema coverage is 100%, so the baseline is 3. The description adds value by explaining the relationship between q and category ('or both'), and instructs how to use dynamic facets from the response with 'filter=facet_key:option_key'. It also clarifies that price and stock have dedicated parameters. This goes beyond the schema's basic descriptions and helps the agent use parameters effectively.

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 clearly states the tool's purpose: 'Search Boots UK products and categories.' It specifies the resource (Boots UK) and action (search), and notes it returns product cards and facets. However, it does not explicitly differentiate from sibling tools like boots_suggest, so it loses a point for not distinguishing itself.

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?

The description gives concrete usage instructions: 'Supply q, one or more hierarchical category keys, or both' and explains how to use repeatable filter values and dedicated price/stock controls. It provides clear context for calling the tool, but it does not mention when not to use it or suggest alternative tools, so it falls short of explicit when/when-not guidance.

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