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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the tool's scope (only 6 most common non-conformities), the response structure (immediate action, PMS documentation, deadlines, DDPP alert conditions, example), and the optionality of the filter. This is useful context, though it does not address error handling or side effects.

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?

The description front-loads the main purpose and uses detailed specifics to convey what the tool returns. The bilingual redundancy is a minor inefficiency, but each sentence provides substantive value, making it appropriately concise for the tool's complexity.

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?

Despite lacking an output schema, the description thoroughly specifies the return content: non-conformity types and the exact fields for each (immediate action, documentation, deadlines, DDPP alerts, example). Given only one optional parameter and full schema documentation, this is complete enough for correct selection and invocation.

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?

The input schema describes the sole parameter exhaustively, listing allowed values and default behavior when absent (schema coverage 100%). The description only restates that the parameter is optional, adding no new meaning. Baseline 3 is appropriate when the schema does the heavy lifting.

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 identifies the tool as returning regulatory corrective actions for six specific non-conformities, enumerating all six and the detailed content of each response (immediate action, documentation, deadlines, DDPP alert conditions, example). This distinguishes it from sibling tools focused on temperatures, DLC, and HACCP plans.

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 the usage context—when you need corrective actions for catering non-conformities—but it does not explicitly state when to prefer this tool over siblings or provide exclusions. The mention of an optional filter is a parameter hint, not usage guidance.

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