Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official

chick_fil_a_menu_taxonomy

Retrieve Chick-fil-A menu taxonomy terms to identify valid filter IDs for menu API queries. Returns each term's ID, name, slug, parent, and menu item count.

Instructions

List one Chick-fil-A menu taxonomy's terms. Returns one page of terms for a single Chick-fil-A menu taxonomy, with each term's id, name, slug, parent and how many menu items carry it. This is how to discover the filter ids GET /chick-fil-a/menu accepts. taxonomy must be one of menu_taxonomy (customer-facing menu section -- Breakfast, Beverages, Catering Entrées, ... 36 terms), menu_item_type (ITEM, ITEM_GROUPING, MODIFIER -- 3 terms), menu_item_group (the grouping a variant belongs to, e.g. "Bacon, Egg & Cheese Biscuit" -- 100+ terms), or nutrition_table_menu (the grouping used by Chick-fil-A's published nutrition tables -- 18 terms). Terms come back alphabetically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number (default 1)
per_pageNoTerms per page, 1-100 (default 20)
taxonomyYesWhich taxonomy to list. One of menu_taxonomy, menu_item_type, menu_item_group, nutrition_table_menu.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

A4.7/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that results are returned alphabetically)Skip, which is a meaningful behavioral detail. It also notes that terms come with counts and that each taxonomy has a fixed number of terms (e.g., 36 terms, 3 terms), giving the agent a sense of expected output size. However, it does not mention pagination details like header links or whether the response includes total counts, but the schema already covers page/per_page. This is good but could mention more about edge cases (e.g., invalid taxonomy).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the purpose and then lists the taxonomies with examples in parentheses. Every clause adds value: it explains what is returned, why it's useful (for menu filters), and enumerates each taxonomy with context. No wasted words. It's concise while being informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (simple list endpoint with one required param) and that the schema fully describes the parametersтные, the description is complete. It explains the return fields, the allowed taxonomy values, and even the ordering (alphabetical). It doesn't have an output schema, but the return fields are described. There is no missing critical information for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%(each parameter has a description), so the baseline is 3. The description adds significant value beyond the schema: it elaborates on each taxonomy value's meaning and term count, which is not in the schema. For example, 'menu_taxonomy' is described as customer-facing sections with examples and count, which is more helpful than just the enum list. However, it does not add details on the 'page' or 'per_page' parameters beyond that, but the schema already explains those. Overall, it exceeds the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to list terms of a specific Chick-fil-A taxonomy, with a detailed enumeration of what each term includes (id, name, slug, parent, menu item count). It explicitly differentiates between the four allowed taxonomy values and their respective contents, which helps disambiguate from related tools like 'chick_fil_a_menu_taxonomy' and 'chick_fil_a_menu_item'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly explains when to use this tool: it is 'how to discover the filter ids GET /chick-fil-a/menu accepts', and it enumerates each taxonomy option with its purpose (e.g., 'customer-facing menu section', 'grouping a variant belongs to'). This gives clear context for which taxonomy to pick based on the desired data, but it does not mention when not to use it, so it's not perfectly complete but still strong.

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

Install Server

Other Tools