chipotle_menu_metadata

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

With no annotations, the description carries the full burden. It discloses what data is returned and, importantly, what is not (prices). It explains the structure of categories, items, sections, groups, and dietary tags. It does not mention potential side effects, rate limits, or auth, but for a read-only metadata endpoint, the absence is minor. It adds context beyond the bare schema by explaining the join for prices and the uniqueness of the data.

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 detailed and informative, but not excessively verbose. It front-loads the purpose and then systematically explains each data component. It uses a concrete example (cauliflower rice) to illustrate aliases. Slight redundancy in repeating 'menu presentation metadata' at the start, but overall it's well-structured and earns its length.

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?

Given the complexity of the data (categories, items, sections, groups, dietary tag taxonomies), the description covers all these aspects clearly. It also explains the relationship to price endpoints and how to join. There is no output schema, so the description appropriately details the content. It is complete for an agent to understand what this tool returns and how to use it.

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%, with both parameters (region and channel) fully documented in the schema, including allowed enums. The description does not add any additional meaning or usage guidance for these parameters beyond the schema, so the baseline 3 is appropriate.

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 clearly states the tool's purpose: 'Get Chipotle's menu presentation metadata' and elaborates on exactly what that includes (categories, items, sections, groups, dietary tags). It explicitly differentiates from other Chipotle endpoints by claiming 'the data no other Chipotle endpoint carries' and mentions the join to /chipotle/menu for prices, distinguishing it from price-focused tools.

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 provides context on when to use this endpoint: it's for metadata (nutrition, dietary tags, customization) and explicitly says it has no prices, directing users to join with /chipotle/menu or /chipotle/restaurant/menu for prices. However, it does not explicitly name alternative sibling tools (e.g., chipotle_ingredients, chipotle_meals) or state clear exclusion conditions beyond the price distinction, so it's strong but not fully explicit.

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