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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds only a list of returned fields, which overlaps the existing output schema rather than disclosing new behavioral traits such as error behavior for unknown ids.

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?

Two sentences, front-loaded with the return payload and followed immediately by the trigger condition and examples. No redundant or filler text.

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 a full output schema and complete annotations, the description supplies the trigger condition and the returned shape. It is essentially complete, with only the untested edge case of an unknown rule_id left implicit.

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% and the parameter is fully documented in the schema, including the same example ids. The description adds no format or resolution semantics beyond what the schema already provides, so the baseline of 3 applies.

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 clear verb (return/look up) and resource (rule/analyzer) and enumerates the specific fields returned (kind, description, severity, detection method, threshold). It is specific enough to distinguish purpose from a generic lookup, but it never contrasts itself with siblings like request_rule or explain_symptom.

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?

Gives explicit when-to-use guidance: 'Call this when a user asks what a specific rule does' with concrete example ids. It stops short of naming exclusions or pointing to an alternative tool, so it is clear context without routing.

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