HealthLedger MCP

Add a biomarker

add_biomarker

Store biomarker observations including oncology, genetic, and inflammatory markers with values, categories, and reference ranges for health tracking.

Instructions

Store a biomarker observation, including oncology/genetic/inflammatory markers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "biomarker": "<biomarker>",
      "value": "<value>"
    },
    "name": "add_biomarker"
  }
}

Input Schema

Name	Required	Description	Default
`flag`	No
`unit`	No
`user`	No
`notes`	No
`value`	Yes
`source`	No
`ref_low`	No
`category`	No
`ref_high`	No
`ref_text`	No
`biomarker`	Yes
`measured_date`	No
`numeric_value`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 9, 2026

TDQS

C2.8/5.0

Behavior2/5

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

Annotations already indicate a write operation (readOnlyHint=false) and non-idempotent behavior, but the description adds no further behavioral context (e.g., whether duplicates are allowed, required permissions, or relationship to existing records).

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?

Single sentence, no redundancy. However, given the tool's complexity, a slightly longer description could improve completeness without sacrificing conciseness.

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

Completeness2/5

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

For a tool with 13 parameters and no schema descriptions, the description is too sparse. It lacks context on parameter usage, expected values, and output behavior, despite the existence of an output schema.

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

Parameters1/5

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

Schema coverage is 0% and the description does not elaborate on any parameters. Despite having 13 parameters, the description provides no additional meaning beyond parameter names, which is insufficient for correct usage.

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?

Clearly states the action ('store') and resource ('biomarker observation'), with specific examples of biomarker types (oncology/genetic/inflammatory). This distinguishes it from siblings like add_lab_result or add_genomic_record.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives such as add_lab_result for standard lab tests or add_genomic_record for genomic data. Agents must infer usage from the purpose alone.

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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