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

With no annotations provided, the description carries the full burden and does well: it discloses that answers come strictly from the attested fact passport, that each returned fact includes source, attestation status, and validity dates, and that a refusal means the passport lacks the fact — the engine never guesses. This is rich behavioral disclosure covering correctness and failure semantics.

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?

Three sentences deliver the core purpose, the key input constraint, the provenance model, and the refusal behavior — all front-loaded and free of filler. Every sentence earns its place.

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 no output schema and no annotations, the description covers purpose, input limits, return semantics, and error behavior, which is strong. The main gaps are the undefined 'entity_domain' parameter and the lack of explicit comparison to sibling tools such as get_passport, but these are minor given the otherwise complete invocation picture.

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 description coverage is 0%, so the description must compensate. It explains the 'question' parameter (natural-language, max 2000 characters) and implicitly ties it to the passport, but 'entity_domain' receives no added meaning beyond its name. Since one of two parameters is effectively undocumented, the compensation is only partial.

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 specific verb and resource: 'Ask a natural-language question about an entity.' It also conveys the answer mechanism (built from the entity's attested fact passport) and refusal semantics, which clearly differentiates it from the sibling tools like get_passport or search_entities even without naming them.

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 implies usage context: use this tool to get a natural-language answer grounded in the fact passport, rather than the raw passport itself. However, it never explicitly states when to prefer ask over get_passport or how it relates to the sibling tools, so the guidance is implied rather than explicit.

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