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

No annotations are provided, so the description must carry behavioral context. It discloses the data source, example returned facts, and a 1-credit cost, but does not state read-only intent, rate limits, ambiguity handling, or error behavior; adequate for a simple lookup, but incomplete.

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 a single front-loaded sentence with a compact fact list and cost. There is no filler, and every element is useful for selection.

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 simple two-parameter lookup, the description gives enough to understand the returned fact categories. However, it lacks input guidance for choosing between id and query, and with no output schema it only lists examples rather than explaining the returned structure.

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 100%, so the schema already documents both parameters. The description adds entity-type context but does not clarify the relationship between the id (Q-id) and query parameters, nor what query accepts, so it only meets the baseline.

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 identifies the data source (Wikidata), the entity types (company, person, place), and concrete fact categories such as headquarters and CEO. It is clear what the tool retrieves, though it does not explicitly mention lookup by Q-id or name.

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 phrase 'structured facts' implies use when structured entity data is needed, but there is no explicit when-to-use or when-not-to-use guidance. It also does not mention alternatives such as wikipedia_summary or company_profile, so the agent must infer when this tool is preferable.

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