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

With no annotations provided, the description carries the full disclosure burden. It usefully reveals the scope ('every bag... on sale in New Zealand') and the sort order ('cheapest per 100g first'), but it does not mention pagination, default stock filtering, or response shape.

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?

Two sentences with no filler. The search scope and ordering rule are front-loaded, and every clause adds information relevant to calling the tool correctly.

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?

The description covers scope, filters, and ordering, which is good for a search tool. However, with no output schema and no mention of pagination, limit defaults, or result format, an agent cannot fully predict what the tool returns or how many results to expect.

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 low (38%), so the description adds some value by clarifying that the free-text query covers name, roaster, origin, and tasting notes, and by listing filterable dimensions. However, it does not clarify the difference between max_price_nzd and max_price_per_100g or the behavior of limit and in_stock_only.

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'), a precise resource ('every bag of specialty coffee on sale in New Zealand'), the available filter dimensions, and the result ordering. This clearly distinguishes the tool from siblings like best_deals and roaster_info even without naming them.

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 use case is implied by the search-and-filter phrasing, but there is no explicit guidance on when to prefer this tool over best_deals or roaster_info, nor when not to use it. An agent would have to infer the boundary from tool names alone.

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