Resolve a supplement identity. Use mode='supplement_retail' only for raw retail product titles; it invokes the fail-closed retail front door. Identity mode is the default.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Explicit routing mode; retail titles require supplement_retail | identity |
| query | Yes | Supplement identity or raw retail product title |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral transparency. It adds value by mentioning that the retail mode is 'fail-closed' and that identity mode is the default. However, it does not disclose return format, error handling, or whether the operation is read-only. This is enough for a basic understanding but lacks comprehensive behavioral detail.
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 exceptionally concise: two sentences, front-loaded with the primary purpose. Every sentence contributes meaningful information—the core function, the mode-specific usage, and the default behavior. There is no redundancy or filler.
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's simplicity (2 parameters, no output schema), the description covers the main usage and mode selection. However, because there is no output schema, the description does not help the agent understand what the tool returns (e.g., a list, an ID, or an entity). It also lacks guidance on when to prefer this tool over sibling tools. While it is adequate for invocation, it leaves gaps in the agent's full understanding.
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 provides 100% coverage for both parameters, including descriptions for 'query' and 'mode'. The description complements this by explaining the purpose of the 'supplement_retail' mode and reinforcing the default. It adds contextual meaning to the 'mode' parameter beyond the schema's enum description, which is helpful for correct invocation.
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: 'Resolve a supplement identity.' It specifies a particular action ('resolve') on a resource ('supplement identity'). It also differentiates between identity mode and supplement_retail mode, which helps distinguish it from other supplement-related tools, though it does not explicitly name sibling 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 gives explicit guidance on when to use the 'supplement_retail' mode: only for raw retail product titles, and notes that it 'invokes the fail-closed retail front door.' It also states that identity mode is the default, implying typical usage. It does not mention when to use this tool over sibling tools, but the mode-specific instructions are clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resource-action pairs, but get_supplements_for_biomarker and get_interventions_for_biomarker overlap in purpose (both return things affecting a biomarker), with the key difference being intervention type filtering. This could cause misselection if the agent does not read descriptions carefully.
All tools follow a consistent verb_noun pattern using snake_case (get_* and search_*). Naming is predictable and clearly groups resource types, with no mixed conventions or vague verbs.
With 9 tools, the set is well-scoped for a supplement and biomarker information server. Each tool addresses a distinct functional need without redundancy, falling comfortably in the ideal 3-15 range.
The tool surface covers the primary workflow: searching supplements/conditions, retrieving supplement details and biomarkers, finding supplements/interventions for biomarkers, checking interactions, and getting brand quality data. Minor gaps exist, such as no direct biomarker search or tool to get conditions for a supplement, but core use cases are covered.