HealthLedger MCP

Analyze wearable trend

analyze_wearable_trend

Read-onlyIdempotent

Analyze trends in wearable health data for a specific sample type over a time range. Returns descriptive statistics with optional source and user filters.

Instructions

Return descriptive stats/trend for one wearable sample type.

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": {
      "sample_type": "<sample_type>"
    },
    "name": "analyze_wearable_trend"
  }
}

Input Schema

Name	Required	Description	Default
`user`	No
`since`	No
`until`	No
`source_id`	No
`sample_type`	Yes

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

Behavior3/5

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

The description adds the verb 'Return' which aligns with the readOnlyHint and idempotentHint annotations. However, it does not disclose any behavioral traits beyond what annotations already provide (e.g., what happens if sample_type is invalid, data range handling, or response format). The description adds modest context.

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

Conciseness3/5

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

The description is a single sentence, making it concise but under-informative. It could be expanded to include key parameter notes or usage hints without losing brevity.

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?

Given the presence of 5 parameters, 0% schema coverage, numerous sibling tools, and an output schema, the description is too sparse. It does not explain what 'descriptive stats/trend' entails, how to format the required sample_type, or how results are returned, leaving significant gaps for an agent.

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?

Input schema has 5 parameters with 0% description coverage, and the tool description only hints at the sample_type parameter. No explanation is given for user, since, until, or source_id, leaving the agent to guess their purpose and formatting.

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 states it returns descriptive stats/trend for a wearable sample type, clearly identifying the resource and action. However, it does not differentiate from similar sibling tools like analyze_biomarker_trend or analyze_lab_trend, which could confuse an agent when multiple trend tools are available.

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 is provided on when to use this tool versus alternatives, such as other analyze_* tools or list_wearable_samples. The description lacks any context about prerequisites, exclusions, or typical use cases.

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

Deploy Server