chick_fil_a_content

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

With no annotations present, the description carries the transparency burden, and it delivers: it discloses pagination ('returns one page'), default response shape (titles, links, publish dates, excerpts), the large-body tradeoff (a 22KB press release, several hundred KB for 20 bodies), and the fact that downloadable assets never include a body. This tells the agent exactly what behavior to expect without requiring a call.

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?

Every sentence carries distinct information—purpose, corpus inventory, exclusivity claim, and the size rationale for bodies—with no repetition of the schema. The most decision-relevant facts (what the tool is and how to choose a corpus) come first.

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 covers the essentials: what fields come back by default, what `include_body` changes, what each type returns, and how pagination works. It could slightly extend to ordering or response envelope details, but the schema already provides per-parameter semantics, so nothing critical is missing for correct invocation.

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?

Although the schema already documents all five parameters, the description adds real meaning: it defines every `type` enum value with precise counts and content examples, explains why `include_body` defaults to false with concrete size numbers, and reveals the default page size. This is substantial value beyond the schema field descriptions.

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—'Browse Chick-fil-A press releases, legal documents and press-kit assets'—and immediately distinguishes the tool from menu/restaurant tools by claiming it covers every content-bearing corpus outside those catalogs. It also enumerates the five type sub-corpora with counts, leaving no ambiguity about what this tool is for.

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?

It identifies clear contexts for use: this is the tool for editorial content (press releases, stories, corporate pages, legal, and downloadable assets) and explicitly excludes menu and restaurant catalogs. It stops short of naming sibling tools like chick_fil_a_faq as alternatives, but the boundary is unambiguous and the type field is thoroughly explained, so an agent knows when to invoke it.

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