Supplement Protocol

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

Annotations already declare the tool as readOnly, destructive, and idempotent. The description adds value by specifying the genes analyzed and that it returns personalized suggestions. No contradictions with annotations; the description enriches the behavioral context beyond the structured fields.

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, well-structured sentence that front-loads the key action and resource. It names specific genes and the output, with no extraneous information. Every word earns its place.

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 tool has no parameters and annotations are present, the description is mostly complete. However, it lacks details on the output format (e.g., returns text, scores, or structured data) which could help the agent interpret results. Still sufficient for a simple tool.

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?

With 0 parameters, the schema coverage is 100% and the description does not need to add parameter details. The baseline is 4 according to the rules, and the description provides sufficient context for a parameterless tool.

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 states it analyzes specific genes (MTHFR, COMT, VDR, BCMO1, FUT2, CBS) related to supplement metabolism and returns personalized suggestions. This clearly defines the tool's focus and distinguishes it from sibling tools like check_medication (drug-related) or trait_report (broader traits).

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 tool is for supplement-related queries but does not explicitly state when to use it over alternatives like check_medication or check_risk. No when-not or comparative guidance is provided, leaving the agent to infer based on the tool's name and focus.

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