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

Annotations already declare readOnly, idempotent, closed-world behavior, so the safety profile is covered. The description adds genuinely useful output behavior: the result echoes inputs back, emits plausibility warnings, and includes a required Labreador citation.

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 tight sentences that lead with the core computation and then the returned artifacts. No filler, though the acronym-laden first sentence is dense enough to slow comprehension slightly.

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 no output schema, the description usefully covers return contents (echoed inputs, plausibility warnings, citation) and the optional-vs-required logic for cancer risk. What is missing is guidance on input validity limits or how the sibling pollution_indices differs, but the essentials for calling the tool are present.

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 67%, with the element fields (csf, name, rfdMgPerKgDay, concentrationMgPerKg) individually documented in the schema. The description only adds that cancer risk is optional, which corresponds to the non-required csf field; otherwise it adds nothing beyond the schema.

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 (compute) and names the exact metrics produced (EDI, THQ per element, HI, optional cancer risk) for contaminants in food. This clearly separates it from fit_standard_curve, though it does not explicitly distinguish itself from the more topically similar pollution_indices 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?

No when-to-use or when-not-to-use guidance is given, and neither alternative (pollution_indices, fit_standard_curve) is mentioned. The reader must infer applicability purely from the metrics named.

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