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

With no annotations at all, the description carries the full burden and does substantial work: it discloses the per-call price and rail, what is inside an answer (per-leg sections, factors, A1 absence statement), that legs are never merged or composite-scored, and the privacy behavior that the topic is discarded with only a hash retained. Remaining gaps are operational details like failure modes or latency, which is a modest omission for a read-style paid lookup.

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 price and core contents are front-loaded, which is good, but the remaining text is one long run-on sentence mixing deliverables, exclusions, and licensing notes, forcing the agent to parse dense commas. Every clause is arguably informative, yet the packaging hurts scanability more than it should.

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 paid lookup with no output schema and no annotations, the description spells out the shape of the return payload (per-leg sections, matching entries, factors, absence statement) and the non-returned classes, which is close to complete. The missing piece is how legs are selected or what a leg id looks like, which is left entirely to the schema's one-line default note.

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 all three parameters are already documented, giving a baseline of 3. The description adds real meaning for "legs" by enumerating the leg facets (provider, class, licence, attribution, freshness, load state) and confirming the topic is discarded, but it says nothing about question_class, so it does not exceed the baseline enough to warrant a 4.

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 the action ("one query-index lookup") and the resource (per-topic, per-leg answer sections) with enough detail that an agent knows it returns data for a submitted topic. It does not name or contrast with the obvious siblings query_index_criteria and query_index_precheck, so the differentiation is left to inference rather than stated.

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?

There is no explicit "use this when" statement and no routing to alternatives such as query_index_precheck before a paid lookup. The scope of exclusions (no A1 data, no Radar API, no WildChat prompts) narrows expectations, but an agent gets no guidance on when to choose this tool over its siblings or on prerequisites before spending $0.01.

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