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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safe-read profile is covered. The description adds genuinely new behavioral context: an unknown rule number is refused and the known numbers are listed, which tells the agent how failure is surfaced.

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, front-loaded with the entity-type scope and input requirement, with no filler. It is dense rather than padded, though the parenthetical sibling references interrupt the flow slightly.

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 single-parameter read tool with an output schema, the description covers scope, input source, and error behavior. Since an output schema exists it needn't enumerate return fields, so the listed return values are redundant but harmless.

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 the baseline is 3, but the description adds real meaning beyond the schema — it states the value is a number sourced from list_rules and that it is accepted in either case, which the schema does not mention. That case-insensitivity detail is a meaningful parameter behavior enhancement.

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 resource precisely — one vocabulary convention of type `rule` — and explicitly distinguishes it from a company's own rule, naming sibling entity tools. The verb is only implied by the name rather than stated, so it falls just short of a crisp verb+resource pairing.

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?

It tells the agent the input must be a number drawn from list_rules (e.g. R9) and points to list_entities/get_entity for the entity distinction, giving clear context for when this tool applies. It does not spell out exclusions or an explicit alternative when the input is not a rule number, but the sourcing requirement covers most selection ambiguity.

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