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

Annotations already indicate a safe, read-only, idempotent operation. The description adds substantial behavioral context beyond that: it requires an API key (with exact authorization formats), explains the no-key teaser and trial offer, states the data source and update cadence, and mandates citation and checked_at reporting. This is exemplary disclosure.

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 longer than average, but every sentence adds necessary operational information: what it returns, data provenance, authentication, fallback behavior, and attribution requirements. It is front-loaded with the core function before moving to supporting details, so the structure is effective for an agent scanning for relevance.

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 fully enumerates the return value categories and adds all contextual requirements (API key, teaser, citation, checked_at, data source, update frequency). For a tool with one parameter and no output schema, this definition leaves no critical gaps an agent would need to invoke 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 has 0% description coverage for its single parameter, but the description compensates by explaining 'shopping list (barcodes and quantities)', mapping directly to the 'items' array and its barcode/qty fields. It also clarifies the domain meaning of the parameter, which goes beyond the raw 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?

The description uses a specific verb ('returns') and names multiple concrete outputs: total per chain, cheapest chain, saving versus most expensive, chains missing items, and best split. It clearly identifies the resource (shopping list of barcodes and quantities) and distinguishes itself from siblings by focusing on basket-level comparison across chains.

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: use this when you have a shopping list of barcodes and want to find the cheapest chain and potential savings. It does not explicitly name sibling alternatives or state when not to use it, but the input format and purpose are unambiguous enough to guide selection.

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