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

Annotations already cover safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false), and the description adds behavioral context beyond them: results are filtered to shops that 'actually have offers in the user's region', limited to 20, formatted as 'Name (ID)', and the caller must pass exact strings into search_offers. The only minor gap is that return-limit/format overlap partly with what an output schema would convey.

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 dense but every sentence earns its place: scope, routing rule, exclusion, return format, downstream chaining, and parameter semantics. It is front-loaded with the core purpose before the usage caveats. Slightly longer than minimal, but the sibling-routing and format-convention details justify the length.

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 simple one-parameter tool, this description is complete: it covers the main failure modes (confusing shops with producers, misusing the returned names), explains the region scoping, and documents the downstream integration with search_offers's shop_names. The output schema handles return structure and annotations handle safety, leaving no material gap 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?

Schema coverage is 0%, so the description carries the full burden for the query parameter. The Args section ('Shop name or partial name the user mentioned') plus the inline examples (Waitrose, Majestic, Tesco) add real meaning beyond the bare schema field titled 'Query'. It doesn't address edge details like case sensitivity, but with a single simple parameter it is nearly sufficient.

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 and resource ('Search for wine RETAILERS / STORES by name') and clearly scopes it to the user's marketplace region. It explicitly distinguishes itself from siblings by naming what it is NOT for (producers, châteaux, domaines, wineries, brands), so an agent can reliably tell it apart from search_offers.

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 an explicit trigger condition ('Call this ONLY when the user explicitly names a retail store'), an explicit exclusion condition ('Do NOT call it for wine producers...'), and names the exact alternative ('those go in the "query" of search_offers'). This is model guidance for when-to-use versus when-not-to-use.

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