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).
| Name | Required | Description | Default |
|---|---|---|---|
| marker | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=true annotations already signaling a safe read operation, the description adds useful context by specifying the output content (reference range and lifestyle plan) and the 'ACLM-optimized' qualification. It does not disclose how to handle unknown markers, but the read-only nature is consistent.
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 a single, well-structured sentence that front-loads the action ('Look up') and the result (reference range and lifestyle plan). The parenthetical examples add value without bloating the text.
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 simple one-parameter lookup tool, the description adequately conveys what is returned and gives examples. However, without an output schema, it does not describe the exact response structure or error handling for unsupported markers, leaving a minor gap.
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 schema provides only a 'marker' string with no description, giving 0% schema coverage. The description compensates by listing concrete example values (apob, lp_a, hscrp, etc.), which clarifies the expected input format and accepted biomarkers.
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 function: looking up an ACLM-optimized reference range and lifestyle intervention plan for a single biomarker. It provides specific examples (apob, lp_a, etc.) and the 'single biomarker' scoping distinguishes it from the sibling interpret_labs tool.
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 for single-biomarker reference lookups through its examples and 'single biomarker' phrasing. However, it does not explicitly mention when to prefer this over interpret_labs or state exclusions, so it lacks a direct alternative comparison.
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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The two tools have clearly distinct purposes: one interprets a full panel of lab values, while the other provides reference ranges for a single biomarker. There is no ambiguity in selecting between them.
Names are consistently lowercase with underscores, but the pattern differs: 'interpret_labs' is verb_noun while 'marker_reference' is noun_noun. Minor deviation, but the style is predictable and readable.
With only two tools, the surface feels thin, but it aligns with a focused lab-interpretation domain. The count is borderline but not unreasonable for the stated purpose.
The domain is lab interpretation, and the tools cover both panel-level interpretation and single-marker lookup. Minor gaps exist (e.g., no direct tool for comparing historical results), but core workflows are supported.