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

With no annotations provided, the description fully carries the behavioral disclosure burden. It thoroughly details limitations (partial, non-exhaustive), metadata semantics (internal taxonomy, not clinical verification), and data usage caveats (pathway_tags raw, dose_mg legacy). This goes well beyond a basic functional statement.

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 dense but every sentence provides essential context for correct use, including exclusions, metadata caveats, and data handling notes. It is structured with front-loaded purpose and subsequent caveats, making it highly informative without unnecessary fluff.

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 absence of an output schema and annotations, the description is remarkably complete: it explains what the tool returns (partial supplement lists), what fields mean (type labels, graph_status, pathway_tags, dose fields), and important limitations. This is sufficient for an agent to set expectations and avoid misuse.

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 input schema already covers both parameters with full descriptions (100% coverage), so the baseline is 3. The description adds no input parameter semantics beyond the schema; its mention of dose_value/dose_unit relates to output fields, not input parameters.

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 the tool's purpose: find supplements affecting a biomarker, with specific scope (registry-classified in Aviado's graph) and explicit exclusions. This distinguishes it from siblings like get_biomarkers_for_supplement (inverse) and get_interventions_for_biomarker (broader).

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 usage when you need supplements for a biomarker and specifies exclusions, but it does not explicitly mention alternatives or when-not-to-use conditions. No direct comparison with sibling tools is provided, leaving the agent to infer the tool's role from context.

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