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Fitatu: Log measurement

fitatu_log_measurement

Fitatu: Add a weight or body measurement for a day to the Measurements tab. Adds one entry to Measurements, such as weight, body fat or a circumference. Fitatu does not import weight from scales or other apps, so this is how a reading from a script reaches the chart. By default you confirm each call; you can switch that off for this tool. Reaches other people: confirm with the user before each call. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDay of the measurement, YYYY-MM-DD. Default: today.
typeYesMeasurement type, e.g. weight, body_fat or waist.
valueYesValue in the unit your account uses.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing the default per-call confirmation behavior (and that it can be disabled), the open-world reach ('Reaches other people'), and the required Cotlet API key scope. These are exactly the operationally important traits an agent needs that readOnlyHint/destructiveHint do not convey.

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?

Front-loaded with the action and its target, then layered with behavior and auth notes. There is mild redundancy between the first two sentences ('Add...' / 'Adds one entry to Measurements'), but no sentence is wasted overall.

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 single-record write with no output schema, it covers purpose, confirmation workflow, reach, and auth. It does not address error or duplicate-entry behavior, but nothing critical for correct invocation is missing.

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%, so the schema already documents date, type, and value with formats. The description's examples ('weight, body fat or a circumference') only loosely mirror the schema's own type examples and add no syntax or unit guidance beyond it, so the schema does the heavy lifting.

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?

States a specific verb and resource ('Add a weight or body measurement ... to the Measurements tab') and immediately characterizes the entry as a single measurement record. This cleanly separates it from sibling read/other-log tools like fitatu_list_measurements and fitatu_log_food without needing to name them.

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?

Explains the context that selects this tool: Fitatu does not import from scales, so this is the path for a scripted reading. It also gives confirmation guidance, but it never explicitly names or excludes an alternative sibling tool, so it falls short of a full when/when-not statement.

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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