chick_fil_a_menu_taxonomy

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 adds useful traits beyond the schema: returns one page of terms, terms come back alphabetically, and each term includes a count of menu items. It does not mention error behavior or auth, but for a read-only list operation the disclosure is solid.

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 but every sentence earns its place: core action, return fields, purpose, and taxonomy breakdown. The most important information is front-loaded, and the taxonomy enumeration is compact yet informative. No filler or repetition.

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 3-parameter tool with no output schema and no annotations, the description is complete: it explains the return shape, pagination, ordering, valid taxonomy values, and the tool's purpose. An agent has everything needed to call it correctly without additional context.

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 baseline is 3. The description adds meaningful semantics beyond the schema by explaining what each taxonomy enum value represents (e.g., menu_taxonomy is a customer-facing section like Breakfast, menu_item_group is a variant's grouping) and by noting term counts. This extra context helps an agent choose the correct taxonomy.

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 specific verb and resource: 'List one Chick-fil-A menu taxonomy's terms.' It clearly states the return fields (id, name, slug, parent, menu item count) and the downstream purpose (discovering filter ids for GET /chick-fil-a/menu). This distinguishes it from sibling tools like chick_fil_a_menu_item and chick_fil_a_locations without needing to inspect 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 explicitly states when to use this tool: 'This is how to discover the filter ids GET /chick-fil-a/menu accepts.' It also enumerates the valid taxonomy values with examples and term counts, which helps an agent pick the right taxonomy. It does not name alternative sibling tools or state when not to use it, 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.