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

Annotations already carry readOnly/idempotent/non-destructive, so the description correctly spends its words on the non-obvious behavior: codes are only exposed where the brand has approved AI assistants, otherwise you get the vouchernaut.com page. That is a real invocation-affecting caveat. It stops short of stating result ordering or what an empty result means, keeping it out of the top band.

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?

Effectively one dense sentence, front-loaded with the search action and the query semantics, with return-shape detail trailing. The parenthetical about AI-approved codes is slightly tangled but earns its place; nothing is padding.

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 no output schema, the description usefully outlines what each store record contains (live code/deal counts, best offers with tracked links, shop link, vouchernaut page) and the code-vs-page caveat. Missing only result ordering/pagination and empty-result behavior, which are minor for a 2-param read tool with full annotation coverage.

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 coverage is 100%, so the baseline is 3, but the description adds real semantic value by clarifying that query accepts either a brand name ("Currys") or a product/category concept ("flowers", "phone cases") — the schema only says 'a store name or what's being bought'. The limit/maximum behavior is left to the schema, which is fine.

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+resource with scope: search UK stores listed by Vouchernaut, by name or category, with concrete query examples. It is distinguishable from siblings like get_store_offers (fetching offers for one store) and search_products (buying something, not a brand/category lookup).

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 is implied by the phrasing (find a store, then presumably use get_store_offers), but the description never says when to pick this over get_store_offers or search_products, nor does it mention there is no alternative for category browsing. Adequate but leaves routing to inference.

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