audit_nlu

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

Annotations indicate read-only, open world, idempotent, non-destructive. Description adds that checking overlap is optional and slower, requiring a projectId. No contradiction with 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?

Two sentences with no wasted words. First sentence states purpose, second gives usage and optional feature. Very concise.

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?

Covers purpose, usage, and key behaviors given the tool's moderate complexity. No output schema, but description doesn't need to explain return values. Slight lack of detail on what the audit exactly returns (list of issues?), but 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 describes all 4 parameters with 100% coverage. Description adds context for projectId: 'Required if checkOverlap=true'. For flowId and minSentences, it adds no new info beyond schema, but overall adds value.

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?

Description clearly states it audits NLU quality for a flow, identifies intents with too few training sentences, disabled intents, and optionally overlapping intents. This distinguishes it from sibling tools like list_intents or get_intent which only retrieve data.

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 tells when to use: 'Use this before deployment to ensure NLU quality.' No explicit when-not-to-use or alternatives, but the deployment context provides clear guidance.

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