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Thecimal

Quantified Self MCP Server

read_health_data

Retrieve daily health metrics—steps, sleep, resting heart rate, weight, workouts, mood, and water intake—for any date range from your local SQLite database.

Instructions

Read daily health metrics from the local database: steps, sleep hours, resting heart rate, weight (kg), workout minutes, mood, and water intake (ml).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoLast day to include, formatted YYYY-MM-DD. Defaults to today.
start_dateNoFirst day to include, formatted YYYY-MM-DD. Defaults to 30 days before end_date. Ranges over ~10 years are rejected.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv1.0.3
    • changedInput schema / properties / start_date / description
      Previous value: -"First day to include, formatted YYYY-MM-DD.\n        Defaults to 30 days before end_date."New value: +"First day to include, formatted YYYY-MM-DD.\nDefaults to 30 days before end_date. Ranges over ~10 years are rejected."
  2. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the burden. It clearly indicates the operation is a read from a local database, implying no mutation, and enumerates the data domains. It does not disclose potential behaviors like pagination, empty-result handling, or timezone assumptions, but output schema plus 'read' cover the essential safety profile.

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?

A single, front-loaded sentence states the operation, source, and the complete list of metrics with units. There is no filler or repetition of schema details.

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 read tool with no required parameters, a rich input schema, and an output schema, the description is nearly complete: it identifies the source and the returned metric categories. The main missing piece is explicit routing guidance versus siblings, which was already penalized under usage guidelines.

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 start_date/end_date parameters have detailed descriptions including format, defaults, and the ~10-year restriction. The tool description itself adds no parameter-level information, so the baseline of 3 applies.

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 uses the specific verb 'Read' with a clear resource, 'daily health metrics from the local database', and lists the exact metrics included. This differentiates it from the write/delete siblings log_daily_metric and clear_metric.

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?

The description gives no explicit guidance on when to choose this tool over its siblings, such as 'use for retrieving metrics as opposed to logging or clearing them.' Although the name implies a read operation, no when-to-use or exclusion criteria are stated.

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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