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

Annotations already establish the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds substantial context beyond them: scores are computed live rather than cached, null means no data, and recommended_strategy is advisory only with strategy_applied always false. That last point is exactly the kind of side-effect clarification an agent cannot get from annotations.

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?

Purpose is front-loaded in the first sentence, then return semantics are grouped by field, then signal sources, then interpretation. Every sentence carries information an agent needs; nothing is filler or restated.

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?

There is no output schema, so the description carries full burden for return values and it delivers: direction and range for each score, null semantics, the advisory nature of recommended_strategy, the structure of `signals`, and the category list the signals cover. An agent can interpret the response without any other source.

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?

The tool takes zero parameters, so the schema baseline of 4 applies and there is no parameter ambiguity for the description to resolve. No further parameter explanation is needed or given.

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 and resource ('get a read-only health report for the user's knowledge base') plus a key qualifier: computed live from the user's own data rather than from static stats. It does not differentiate itself from nearby siblings such as get_world_model_stats or query_world_model, so an agent must infer which diagnostic surface to pick.

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?

Usage is implied rather than stated: the closing sentence ('A high uncertainty or drift score means recalled information is less reliable than usual') hints at when a health check matters, but there is no explicit when-to-use, when-not-to-use, or named alternative. An agent gets a rationale but no routing rule.

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