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

Annotations already declare read-only, idempotent, closed-world behavior, and the description adds what a caller cannot infer: matches are questions with the first sentence of a computed answer from the live dataset, plus URLs to cite and JSON endpoints. It doesn't mention ranking, fallback behavior when nothing matches, or result ordering, which is the remaining gap.

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?

Front-loaded with the verb and purpose, and the example list is genuinely useful for calibration. It is a single dense run-on sentence in the second half, and the parenthetical guide examples could be trimmed without losing meaning.

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?

With no output schema, the description carries the return-value burden and does so: matching questions, first sentence of the answer with live figures, cite URL, JSON URL, and matched guides with their own JSON URLs. Combined with annotations covering the safety profile, an agent has enough to call this correctly.

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 (query, limit with default 3 and max 10) are fully documented there. The description's examples illustrate acceptable query phrasing but add no syntax or constraint detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb+resource ('Find TokenBank answer pages') for a natural-language question, and the concrete example queries make the resource unambiguous. It also implicitly separates itself from siblings by positioning this as the question-entry tool and the others as filters.

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?

'Use this first for a question a person would type; use the other tools to filter beyond it' gives a clear entry-point rule and an exclusion. It stops short of naming which sibling to reach for a structured filter, so the routing is directional rather than precise.

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