kroger_products

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool batches up to 50 products, sources data from Kroger's own API, includes specific return sections, and that location_id scopes price and stock to one store. This is substantive behavioral context beyond the schema, though it does not mention rate limits, failure modes, or exactly how missing location_id affects the response.

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 well-structured, opening with the core purpose and then detailing return contents and the location_id effect. The second sentence is long, but every clause names a distinct data category an agent would care about. No filler or redundant phrases.

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 no output schema and no annotations, the description covers the essential operational details: batch size, source, return sections, sibling differentiation, and parameter scoping. It is slightly incomplete on the behavior when location_id is omitted and on response shape/pagination, but it gives enough for an agent to select and call the tool 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 description coverage is 100%: upcs is documented as comma-separated up to 50, and location_id is documented as the store/location id that scopes price and stock. The description reinforces this by restating the batch limit and clarifying that location_id scopes to 'one store,' but it adds only marginal semantic value beyond the schema.

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 action ('Get full Kroger product detail in bulk'), a clear resource (Kroger products), and a concrete scope (up to 50 products in one call). It explicitly contrasts itself with the sibling kroger_product by enumerating the additional data fields, so an agent can distinguish it without opening schemas.

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 clear context for when to use this tool: when you need bulk Kroger product detail with nutrition, allergens, store-specific pricing/stock, ratings, hierarchy, and images. It names the related kroger-product alternative and explains that this tool carries materially more data. It does not explicitly state when NOT to use it (e.g., for a single lightweight product lookup), so it falls just short of a 5.

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