Get Amino Acid Patterns

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

No annotations exist, so the description carries the full burden, and it does well by disclosing the actual returned content (the nine amino acid values and their units) and framing it as a fixed reference pattern rather than a computed result. It never explicitly states the operation is a side-effect-free static lookup, and there is no mention of caching or any caveat, but the nature of the tool is unambiguous.

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 purpose sentence is front-loaded and useful, but the nine-line enumeration of amino acid values largely duplicates what the existing output schema already conveys, and the six-item use-case list has noticeable overlap (PDCAAS calculation and protein quality evaluation are the same activity). It is well organized but longer than necessary.

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?

For a zero-parameter lookup with a rich output schema, the description gives an agent everything needed: what the data is, what units it uses, and when to reach for it. The only real gap is the absence of guidance about pairing it with the DRI or macro tools in a broader workflow.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies the call needs no input arguments.

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 and resource ('Get amino acid patterns') and pins down exactly which pattern: the PDCAAS reference pattern of indispensable amino acids for 1-3 year old children. That level of specificity clearly separates it from the DRI table siblings (get_macronutrient_dri_tables, get_specific_macronutrient_dri), which serve a different purpose.

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 'Use this tool when' block gives six concrete activation scenarios (PDCAAS calculation, protein complementation, vegetarian diet adequacy, etc.), which is strong positive guidance. It does not, however, tell the agent when NOT to use this tool or point to the DRI siblings as the alternative for requirement comparisons, so the routing is one-sided.

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