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B.O.N.S.A.I. Health Intelligence API

marker_reference

Read-only

Look up the ACLM-optimized reference range and lifestyle intervention plan for a single biomarker (e.g., apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
markerYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds beyond that by specifying the return content (reference range and lifestyle intervention plan) and the ACLM-optimized nature. No contradiction with annotations; the behavior is consistent with a read-only lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that is concise and informative, with no filler. Every word contributes to understanding the tool's purpose and examples.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only lookup tool with one parameter, the description conveys purpose, examples, and return content. It doesn't detail output format or error handling, but with good annotations and no output schema, it's sufficiently complete for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only defines 'marker' as a string with no description. The description compensates by providing six concrete examples (apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d) and clarifying that it's a single biomarker, significantly adding meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'look up' with a clear resource: 'ACLM-optimized reference range and lifestyle intervention plan for a single biomarker.' It distinguishes itself from sibling tools like interpret_labs and lifestyle_query by focusing narrowly on single-biomarker reference lookup, with concrete examples.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: for a single biomarker reference range and lifestyle plan. It doesn't explicitly mention alternatives or exclusions, but the single-biomarker scope provides clear context, aligning with a 'clear context, no exclusions' level.

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

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