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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it excels. It details that unavailable publishers are returned in `unavailable` and never charged, that monthly AI answers subscriptions cover only articles from the start date, that include_archive adds the full catalogue, and that the returned access key works only once paid via hosted_invoice_url. It also states the requirement for terms acceptance. This is comprehensive transparency.

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 long but every sentence carries essential information. It front-loads the core purpose, then systematically covers licence options, billing modes, edge cases, return values, and prerequisites. There is no redundancy or fluff; the density is appropriate for the complexity of the operation.

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?

The description is fully self-contained: it explains the return payload (order, lines, access key, hosted_invoice_url), the prerequisites (buyer session, terms_accepted), and the edge cases (unavailable publishers, include_archive behavior). Without an output schema, it provides all necessary context for an agent to call the tool correctly and interpret results.

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, but the description adds substantial meaning beyond the schema. It explains the semantic differences between licences (enterprise vs archive vs training vs display), the allowed billing modes per licence, the quantity constraint for display, the publisher limit of 18 for metered, the include_archive behavior, and the terms_accepted requirement. This transforms the parameter documentation from structural to behavioral.

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 clear verb and resource: 'Place a licence order with Opedd for one or more publishers.' It then precisely defines the one-order-one-licence model, enumerates the four licence types with their billing modes, and explains the per-publisher Schedule pricing. This level of specificity fully distinguishes the tool's purpose from any sibling without ambiguity.

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 operational context: it states the prerequisite of a buyer session (OPEDD_BUYER_JWT) and the mandatory terms_accepted flag, and it explains the behavior for unavailable publishers. However, it does not explicitly mention alternatives or exclusions (e.g., when to prefer purchase_license). The context is sufficient for an agent to infer appropriate use, but lacks explicit routing to sibling tools.

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