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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is fully covered. The description adds that output includes rules plus their fixes, but since an output schema exists this is largely redundant rather than genuinely new behavioral context.

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, both carrying distinct information: first the mapping behavior with examples, second the call condition. No filler and the purpose is front-loaded.

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?

With rich annotations, an output schema, and a fully documented single parameter, the description only needs to convey intent and routing, which it does. Nothing an agent needs to invoke it correctly is missing.

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% for the single 'symptom' parameter, which sets a baseline of 3. The three inline examples ('my app is slow', 'hardcoded password', 'infinite react loop') go beyond the schema's terse 'plain-language description' by showing the expected granularity and free-text style.

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 (Map) with both the input resource (natural-language symptom) and the output resource (Code Auditor rule(s) and their fixes), with concrete examples. The clause 'rather than naming a rule' cleanly separates it from the lookup_rule sibling.

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?

Explicitly states the trigger condition ('Call this when a user describes a problem') and the discriminating condition against the alternative ('rather than naming a rule'), which is exactly the decision an agent must make between this and lookup_rule.

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