chick_fil_a_content

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

With no annotations provided, the description carries the full burden and delivers: pagination behavior ('Returns one page'), the downloadable-asset exception (title and link only, never a body), and a detailed performance rationale for include_body (22KB per press release, several hundred KB per default page). It also states the default return fields (titles, links, publish dates, excerpts). This is exactly the kind of behavioral context an agent needs.

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 dense but every sentence earns its place: purpose, corpus enumeration with counts, scope boundary, and the include_body performance trade-off. It is front-loaded with the core purpose before details, and there is no filler or repetition given the absence of annotations and the complexity of the enum parameter.

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 5-parameter tool with no output schema and no annotations, the description covers everything an agent needs: the full type semantics, the return format when body is omitted, the size implications of include_body, and the boundary of what this corpus includes. Combined with 100% schema coverage for the remaining parameters, nothing essential is missing.

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 coverage is 100%, so the baseline is 3. The description adds genuine value beyond the schema by enriching the type enum with corpus sizes (289 press releases, 189 blog articles, etc.) and explaining the include_body default-off rationale and the body-less nature of downloadable assets. It does not add semantics for page, per_page, or search, but those are already well-documented in the schema.

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 names a specific verb and resource ('Browse Chick-fil-A press releases, legal documents and press-kit assets') and enumerates the five distinct corpora with exact counts. It explicitly carves out scope from the menu and restaurant catalogs, which distinguishes it from sibling tools like chick_fil_a_menu and chick_fil_a_locations.

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 scope statement 'every content-bearing corpus Chick-fil-A publishes outside the menu and restaurant catalogs' gives the agent clear context on what this tool covers and what it does not. However, it stops short of naming specific alternative tools (e.g., chick_fil_a_faq, chick_fil_a_menu) or stating explicit when-not-to-use conditions, so it earns a 4 rather than a 5.

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