Dietary Assess Residue Evidence Fit

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds no additional behavioral context beyond the purpose—it does not explain what happens to inputs, whether profiles are validated, or any side effects. Given annotation coverage, this is acceptable but not additive.

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 is a single, front-loaded sentence with no wasted words. It is concise and easy to read. However, its brevity edges toward under-specification, but as a structure dimension, it still earns credit for being clean and unambiguous in form.

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?

Given the complex input schema with rich nested types and an output schema, the description is too sparse to be complete. It does not explain what 'coverage' or 'fitness' mean, what the output represents, or what preconditions are needed (e.g., both residue and consumption profiles must be provided). Annotations cover safety, but the semantic gap remains significant.

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 0%, and the description does not mention any of the parameters beyond the indirect reference to 'residue-profile' which maps to the residue_profile field. The request object also contains consumption_profile and scenario_class, neither of which is hinted at. The schema provides structure but no semantic explanation, so the description fails to compensate for the coverage gap.

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 states a clear verb ('Assess') and resource ('residue-profile coverage and fitness'), which distinguishes it from sibling tools like dietary_build_residue_profile or dietary_apply_residue_evidence. However, 'for the selected dietary workflow' is vague and does not specify what workflow or what 'coverage' and 'fitness' entail, leaving some ambiguity.

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 provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, preconditions, or compare with sibling tools such as dietary_build_residue_profile, dietary_reconcile_residue_evidence, or dietary_assess_review_dossier_readiness. The phrase 'selected dietary workflow' implies a context but gives no concrete direction.

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