Cronometer MCP

get_biometrics

Read-onlyIdempotent

Retrieve a biometric time series such as weight or body fat from Cronometer for a date range, returning daily {day, value} points for tracking and analysis.

Instructions

Get a biometric time series such as weight or body fat from Cronometer.

Returns the recorded values over the date range as a list of {day, value} points.

Use list_biometrics to find metric_id and unit_id (e.g. Weight is metric_id 1, with unit_id 1 for kg or 2 for lbs).

Args: metric_id: Numeric metric ID from list_biometrics. unit_id: Numeric unit ID from the metric's units in list_biometrics. start_date: Start date as YYYY-MM-DD (defaults to 30 days ago). end_date: End date as YYYY-MM-DD (defaults to today).

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": {
      "metric_id": "<metric_id>",
      "unit_id": "<unit_id>"
    },
    "name": "get_biometrics"
  }
}

Input Schema

Name	Required	Description	Default
`unit_id`	Yes
`end_date`	No
`metric_id`	Yes
`start_date`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral detail beyond annotations, including the exact return format ('a list of {day, value} points') and default date ranges (start defaults to 30 days ago, end to today). This enhances the agent's understanding of what to expect without contradicting annotations.

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?

The description is well-structured and appropriately sized: it front-loads the purpose and return format, then provides a useful cross-reference to list_biometrics, followed by a concise parameter list. Every sentence carries meaningful information without redundancy.

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

Completeness5/5

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

Given the tool has an output schema and rich annotations (readOnly, openWorld, idempotent, non-destructive), the description covers all necessary aspects: purpose, return shape, parameter semantics, defaults, and a prerequisite reference. No critical information is missing for an agent to invoke this correctly.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates by explaining every parameter: metric_id is a numeric ID from list_biometrics, unit_id is a numeric unit ID with a clarifying example, and start_date/end_date have format specifications and defaults. This provides meaning far beyond the bare schema properties.

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 begins with a specific verb ('Get') and resource ('a biometric time series such as weight or body fat from Cronometer'), making the tool's purpose immediately clear. It further distinguishes itself from sibling tools like add_biometric, edit_biometric, and remove_biometric by describing a read operation that returns data.

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 description explicitly tells the agent to 'Use list_biometrics to find metric_id and unit_id', which is a clear prerequisite and points to the correct sibling for obtaining required parameters. While it doesn't explicitly enumerate exclusions or alternative retrieval tools, the context is sufficient to understand when this tool is appropriate.

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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