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chick_fil_a_content_taxonomy

List Chick-fil-A category and tag vocabularies with term IDs, names, and counts to use as filters for navigating press releases, stories, legal, and campaign content.

Instructions

List the category and tag vocabularies Chick-fil-A classifies its content under. Returns one page of a content taxonomy's terms, each with its id, name, slug, parent and the number of entries carrying it. Every id is a ready-to-use category or tag filter value on GET /chick-fil-a/content, which is what makes the editorial corpora navigable rather than only pageable. taxonomy selects the vocabulary: press_category (16 terms) and press_tag (96) classify press releases, story_category (9) and story_tag (74) classify blog stories, legal_category (8) and downloadable_asset_category (7) classify those corpora, and campaign (9) is applied across several at once. Terms are ordered by name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page number (default 1)
per_pageNoTerms per page, 1-100 (default 20)
taxonomyYesWhich vocabulary. One of press_category, press_tag, story_category, story_tag, legal_category, downloadable_asset_category, campaign.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / taxonomy / enum
      Added value: +[
+  "press_category",
+  "press_tag",
+  "story_category",
+  "story_tag",
+  "legal_category",
+  "downloadable_asset_category",
+  "campaign"
+]
  2. Addedv1.16.2

TDQS

A4.5/5.0
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 pagination ('Returns one page'), ordering ('Terms are ordered by name'), per-vocabulary term counts, and the relationship to the content endpoint. It does not mention auth or rate limits, but for a read-only list endpoint this is reasonable coverage.

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?

Four sentences, front-loaded with the core purpose, then returned fields, then the taxonomy mapping. Every sentence adds distinct value with no filler or repetition of schema details.

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?

Despite no output schema, the description lists the returned fields, pagination behavior, ordering, and all taxonomy options with counts. It also tells the agent how to use the ids as filters on the content endpoint, making it complete for selection and invocation.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful context for the `taxonomy` parameter by explaining each enum value's corpus and term count, and reinforces pagination with 'Returns one page.' This goes beyond the schema's simple enum listing.

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?

Description opens with a specific verb and resource: 'List the category and tag vocabularies Chick-fil-A classifies its content under.' It enumerates returned fields (id, name, slug, parent, entry count) and distinguishes itself from sibling chick_fil_a_content by explaining these ids are ready-to-use filter values for that endpoint. The name also separates it from chick_fil_a_menu_taxonomy.

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

Usage Guidelines4/5

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

The description clearly states that `taxonomy` selects the vocabulary and maps each enum value to the corpus it classifies (press releases, blog stories, legal, downloadable assets, campaign). It implies when to use this tool: before querying GET /chick-fil-a/content to obtain valid category/tag filters. It does not explicitly name alternatives or exclusions, but the context is strong.

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

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