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LOINC Panel Structure

loinc_panels
Read-onlyIdempotent

Get the structure of a LOINC panel or form.

Use this tool to:

  • See all tests included in a panel (e.g., CBC, metabolic panel)

  • Get the structure of assessment forms

  • Find related observations grouped together

Returns the list of LOINC codes that make up the panel.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loinc_numYesLOINC number (e.g., "2339-0")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
panelYes
loinc_numYes
provenanceYesProvenance block (contract v1.0): source, URL, data vintage, extraction instant, citation, license
attributionYesCanonical source URLs of this response (attribution list)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds that the result is a list of LOINC codes, which is useful but does not disclose any additional behavioral traits beyond the annotations.

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

Conciseness4/5

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

The description is concise and front-loaded with the core action, followed by compact usage bullets and a one-line result statement. It is slightly verbose in the bullets but each contributes useful context.

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 single-parameter, read-only tool with an output schema and strong annotations, the description covers query intent and result shape sufficiently. A small omission is that it does not mention the open-world nature of panel membership, so an agent might assume the returned code list is exhaustive.

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter loinc_num is documented with a pattern and example in the schema. The description itself says nothing further about the parameter, so it adds no semantic value beyond the schema, keeping this at baseline.

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 opens with a specific verb and resource ('Get the structure of a LOINC panel or form') and clarifies the output: the list of LOINC codes that make up the panel. The examples (CBC, metabolic panel, assessment forms) distinguish it from search/detail sibling tools.

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 'Use this tool to' bullets give clear contexts where the tool is appropriate, such as seeing all tests in a panel or getting assessment-form structure. It does not name sibling tools or explicitly state when not to use it, but the intended usage is evident.

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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