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HealthLedger MCP

HealthLedger MCP

by Cole-Will-I-Am
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Analyze biomarker trend

analyze_biomarker_trend
Read-onlyIdempotent

Compute descriptive trend statistics for numeric biomarker observations, allowing you to uncover patterns over time using a specified date range.

Instructions

Return descriptive trend stats for numeric biomarker observations.

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>"
    },
    "name": "analyze_biomarker_trend"
  }
}

Input Schema

NameRequiredDescriptionDefault
userNo
sinceNo
untilNo
biomarkerYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3/5.0
Behavior3/5

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

The description adds context (numeric biomarker observations, descriptive stats) beyond annotations (readOnlyHint, idempotentHint). No behavioral details like data range limits or output format are disclosed, but annotations adequately cover safety.

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?

Single sentence with no wasted words. Clearly communicates core purpose.

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?

With 4 parameters and no schema descriptions, the description is insufficient. It omits details on input constraints (e.g., date format, 'user' meaning) and does not clarify the output format despite the output schema existing.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It mentions 'biomarker' but does not explain the 'user', 'since', and 'until' parameters, their types, or defaults. This leaves significant ambiguity for an AI agent.

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

Purpose4/5

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

The description clearly states the tool returns 'descriptive trend stats for numeric biomarker observations', specifying the action and resource. However, it does not differentiate from other trend analysis siblings like 'analyze_lab_trend' or 'analyze_trend'.

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 (e.g., analyze_lab_trend, analyze_trend). No conditions for use or exclusions provided.

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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