papajohns_intl_offer

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

With no annotations provided, the description carries the full burden. It discloses the nature of the operation (a read-only fetch of offer composition) and details what is returned: price, choice steps, eligible products with surcharges, and ingredient rules. It does not mention any side effects, authentication, or error handling, but the description clearly indicates a non-mutating data retrieval, and it gives a comprehensive overview of the response content, which is sufficient for the agent to anticipate results.

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 moderately long but front-loaded with the core purpose. It uses an example ('pick your family pizza') to clarify the choice-step concept and explains the ingredient rules clearly. Each sentence adds value; there is no redundancy. It could be tightened slightly, but it remains efficient and well-structured.

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?

Given the tool's complexity (two parameters, no output schema, no annotations), the description covers the essential context: it explains the input sources, the output contents, and the scope. It doesn't specify the exact JSON structure or pagination, but since there is no output schema, the description's breakdown of components (price, steps, products, surcharges, ingredient rules) gives the agent a strong understanding of what to expect. It is nearly complete for a simple offer-lookup tool.

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?

The schema already provides descriptions for both parameters (market enum and offer_id with reference to the deals endpoint), achieving 100% coverage. The description adds meaningful context beyond the schema by explaining what the offer_id is (from a deal) and clarifying that the market parameter restricts to the six listed countries. It also explains what the returned data contains, which helps the agent understand the meaning of the offer_id in practice.

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 clearly states the tool's verb, resource, and scope: 'Get one Papa John's offer's composition (international).' It also enumerates the exact markets and explains what the output contains (price, choice steps, eligible products, ingredient rules), distinguishing it from siblings like papajohns_intl_deals (which lists deals) and papajohns_intl_product (which would return product-level data). The purpose is specific and unambiguous.

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 provides clear context for when to use this tool: it explains that offer ids come from the offer_id field on a deal from GET /papajohns/intl/deals, and describes that this tool returns the detailed composition of a single offer. It does not explicitly contrast with alternatives (e.g., papajohns_intl_product), but the scenario is implied well enough for an agent to infer when to call it. Missing explicit 'use this when...' guidance, 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.