Dietary Parse Raw Survey Dataset

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

Annotations already convey read-only, idempotent, non-destructive behavior. The description adds no behavioral detail about validation rules, normalization steps, or error handling. 'Into a governed dataset' is ambiguous about persistence, but not a direct contradiction.

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?

One concise sentence with no filler, and it is front-loaded. However, it is not appropriately sized for a tool with a complex nested schema—it omits essential input details and reads as an under-specified summary.

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?

Description provides only a high-level purpose. The tool has a large nested schema and an output schema, yet no explanation of inputs, validation behavior, or normalization specifics. Inadequate for an agent to invoke correctly without further information.

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%. The description mentions 'raw individual survey consumption records' but does not explain the required top-level parameters (datasetId, regionId, populationGroup) or the structure of rawRecords. It offers minimal value 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?

The description uses specific verbs 'Parse, validate, and normalize' and names the resource 'raw individual survey consumption records' with an outcome 'governed dataset.' It clearly states what the tool does and is distinct from export/lookup siblings, though it doesn't explicitly contrast with sibling check/import tools.

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 guidance on when to use this tool versus alternatives such as dietary_check_adapter_import or import checkers. No prerequisites, exclusions, or context for choosing this over other data-processing tools.

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