Dietary Build Uncertainty Intake Assessment

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 the tool is safe and side-effect-free. The description adds minimal context by promising 'transparent' behavior and 'explicit assumptions,' but it does not specify what assumptions are made or how transparency manifests in the output. No contradiction with annotations exists.

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 sentence with no filler, front-loaded with the action and main subject. It is appropriately short, but the brevity comes at the cost of missing useful context about inputs and assumptions.

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?

This is a complex tool with a large, deeply nested request schema and an output schema, yet the description offers only a one-line overview. It does not orient the agent to the required inputs, the two-dimensional methodology, or the meaning of 'explicit assumptions.' The existence of an output schema reduces the need to explain returns, but input guidance is still inadequate for the complexity.

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 only parameter, 'request', is a complex nested object with numerous subfields. The description does not explain what the request should contain, which fields are important (dataset, residue_profile, uncertainty models), or how to structure the input. The agent must rely entirely on the schema, which is dense and has no descriptive text.

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 a specific verb ('Run') and names the resource ('two-dimensional uncertainty intake assessment') with a qualifier ('transparent ... explicit assumptions'). It distinguishes itself from sibling tools like dietary_build_bounded_intake_summary and dietary_build_probabilistic_intake_summary by focusing on uncertainty assessment rather than summary generation, though it does not explicitly name alternatives.

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 such as dietary_build_bounded_intake_summary or dietary_build_probabilistic_intake_summary. It also fails to mention prerequisites like the need for a dietary survey dataset, residue profile, and residue uncertainty models, which are evident from the schema but not surfaced in the description.

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