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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently describes pricing behavior (8 priced regions with local currency, others fall back to USD/default with metadata), the full set of plans (five-rung ladder plus `cpa` and add-ons), and the returned fields (AI credit allowance, feature bullets, signup URL, provenance). It does not mention auth or rate limits, but for a read-only list tool this is acceptable. The description is honest about fallback behavior and scope.

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 information-dense, with no filler. The first sentence states the core purpose, followed by pricing behavior, plan ladder, return fields, and filtering. It is front-loaded with the most important detail (what it lists) and then elaborates. While it could potentially be trimmed, every sentence adds necessary context for correct usage, so it earns a high score despite length.

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 tool has no output schema, so the description must explain return values, which it does thoroughly (AI credit allowance, feature bullets, signup URL, provenance). It also covers the full plan spectrum, pricing fallback logic, and the distinction from a sibling product. For a tool of this complexity, the description is complete enough for an agent to call it correctly without needing additional context.

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% and both parameters have descriptions, but the tool description adds substantial meaning: it explains the `plan` enum values (free/starter/pro/business/scale/cpa, and that cpa is the Partner Program) and the `country` behavior (which regions have local pricing, fallback for others, and that omitting country returns priced markets). It also clarifies the meaning of the returned fields. This goes well beyond what the schema provides.

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 states a specific verb and resource: 'List HelloBooks pricing plans' with explicit scope (monthly + annual prices, plan ladder, add-ons). It clearly distinguishes itself from the sibling `practice_management_info` by explicitly stating that practice management is a separate product and should NOT use this tool. The purpose is unambiguous and differentiated.

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 explains when to use this tool (to retrieve pricing plans) and explicitly names an alternative (`practice_management_info`) for a specific case. It also tells when to filter by plan or country. However, it doesn't provide a broader 'when not to use' beyond practice management, nor compare against other list tools like `list_credit_packs` or `list_features`. Still, the key alternative is clearly identified.

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