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

Goes well beyond the annotations: it enumerates the exact fields returned per product, states that catalogs are continuously refreshed so prices/stock are current, clarifies that the platform sells nothing itself (the store fulfills), discloses that links carry UTM tags, and gives a rendering instruction for linkLabel. That is substantive operational context the annotations cannot supply.

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?

Front-loaded with what the tool does and how its output differs from web search, then layers operational detail. Sentences are dense and mostly earn their place, though the UTM-commerce paragraph is longer than strictly needed to call 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?

Despite an output schema being present, the description still characterizes result contents, freshness, and attribution/linkLabel handling, leaving no gaps an agent would need before invoking it. Nothing material is missing.

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%, so the schema already documents both query and limit (including default and 1–20 bounds). The description adds only plain-words phrasing examples for query, which is marginal value over the schema; 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?

States a specific verb (searches) and resource (product catalogs of curated independent online stores), and explicitly distinguishes the output from a general web search: it returns products, not pages. An agent can tell immediately what this tool produces without opening the schema.

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?

Gives concrete fit criteria ('find, compare or choose products') with illustrative requests, and states the negative case versus a general web search. It does not, however, mention the sibling find_shop_nobi_page or draw any boundary against it, so routing between the two remains an inference.

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