taco_bell_product

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

With no annotations, the description carries the burden, and it does meaningful work here: it frames the operation as a read-only fetch ('Get', 'Returns'), details what the response will contain, and explains a subtle behavior (negative calorie deltas for Fresco replacements). It does not explicitly state 'no mutation/error behavior,' but the disclosure is strong.

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 front-loaded with the purpose, then systematically covers return fields, the distinctive customization feature, calorie-delta behavior, and slug requirements. There is slight redundancy ('one menu item's full detail' / 'one Taco Bell US menu item in full'), but overall each sentence earns its place.

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, the description compensates well by enumerating the important return elements (product code, name, price, calorie counts, images, cross-sells, customizations) and the accepted input forms. It does not cover error/edge-case behavior, but nothing critical needed for correct invocation appears 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 coverage is 100%, so the baseline is 3. The description adds extra parameter-level value by telling the agent that slugs come from GET /taco-bell/menu and that both bare slugs and full path forms are accepted—information not present in the input 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 opens with a precise verb-resource-object statement: 'Get one Taco Bell menu item's full detail, including its customization matrix.' It distinguishes itself from sibling listing/nutrition/store-menu tools by emphasizing that it returns a single US menu item with complete customization data.

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 clearly implies when this tool is appropriate: when a caller needs full item detail and the customization matrix. It also provides a sequencing hint ('Slugs come from GET /taco-bell/menu') and accepted slug forms. However, it does not explicitly name alternatives or state when to prefer a different sibling tool like taco_bell_menu.

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