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

No annotations are provided, so the description carries the full disclosure burden. It openly lists the kinds of results returned (interaction data, safety score, quality grade, filler detection, NIH verification, timing recommendation), which gives the agent a clear behavioral model. It does not reveal any limitations or underlying data-source behavior, but the read-only 'check' framing is reasonably transparent.

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 compact and front-loaded: the core purpose comes first, followed by return categories and a usage trigger. Every sentence adds value, though the second sentence is a dense list of outputs that could arguably be trimmed or structured better.

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?

There is no output schema, so listing the return categories is important and mostly sufficient. However, the description bundles outputs that appear to belong to sibling tools (quality grade, NIH verification, timing) without clarifying how this tool relates to them or when to call those siblings instead. This creates moderate ambiguity for an agent navigating the full toolset.

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 100%, so the schema already documents all three parameters adequately. The description adds little to parameter semantics beyond echoing the concept of 'existing supplements' and medications, which matches the schema. This is the baseline 3 case where the schema does the heavy lifting.

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 specific verb ('Check'), a clear resource (supplement safety against medications and existing supplements), and lists the outputs returned. It does not explicitly differentiate itself from sibling tools like grade_supplement_quality or get_supplement_timing, even though its output list overlaps with them, so it stops just short of a 5.

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 gives clear trigger conditions: 'Use this whenever a user asks about supplement safety, drug interactions, or whether they can take a supplement with their medications.' It does not state when not to use it or point to alternatives such as verify_nih_label or grade_supplement_quality, which are relevant given the overlapping outputs.

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