Export rule detector mapping

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the context 'from the live registry', indicating the data source, but doesn't elaborate on other behavioral aspects. With annotations present, this is adequate.

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?

A single, front-loaded sentence that conveys the purpose and source without waste. It earns its place with no redundancy or extraneous detail.

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?

The tool is simple (one optional param, no required params) and has an output schema plus thorough annotations. The description, while brief, sufficiently covers the core purpose and source. It could mention the output shape, but the output schema exists, so this is acceptable.

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%. The schema already thoroughly explains the 'languages' parameter, including behavior when omitted and default semantics. The description adds no additional parameter information, which is fine since the baseline is 3 for high coverage.

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 clearly states a specific verb ('Generate') and resource ('rule-detector mapping JSON') with a source ('from the live registry'). This uniquely distinguishes it from sibling tools like detect_languages or generate_prompts.

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 description implies a clear use case: obtaining the current rule-detector mapping. While it doesn't explicitly state when not to use alternatives, the context is clear and no exclusions are needed given the distinct purpose.

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