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eddmann

intervals-icu-mcp

by eddmann

get_wellness_data

Retrieve recent wellness metrics (HRV, sleep, resting heart rate, mood) with configurable lookback; returns JSON summary.

Instructions

Get wellness data for recent days.

Returns wellness metrics including HRV, sleep, resting heart rate, mood, fatigue, soreness, and other health markers.

Args: days_back: Number of days to retrieve (default 7)

Returns: JSON string with wellness data

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
days_backNoNumber of days to look back

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It mentions returning a JSON string with a list of metrics, which is useful, but it does not disclose how `days_back` is interpreted (e.g., inclusive of today, timezone), any error conditions, or whether the operation has side effects. This is a significant gap for a read tool with zero annotation coverage.

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 concise and well-structured: a one-sentence summary, a list of metrics, and clearly labeled Args/Returns sections. It is front-loaded with the primary purpose and contains no unnecessary wording.

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

Completeness3/5

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

For a simple one-parameter tool, the description is reasonably complete but lacks context about its relationship to `get_wellness_for_date` and provides only a vague return type of 'JSON string' without describing the structure. There is no example or clarification on the range semantics, leaving some ambiguity.

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?

The input schema already fully describes `days_back` with a default value and description. The description repeats this information without adding new semantic meaning, so it does not compensate beyond the schema, which has 100% coverage. Baseline 3 applies.

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 retrieves wellness data for recent days and lists the specific metrics included (HRV, sleep, resting heart rate, mood, etc.). However, it does not explicitly differentiate from the sibling `get_wellness_for_date`, though the phrase 'recent days' implies a range rather than a single date.

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 provides no guidance on when to use this tool versus alternatives like `get_wellness_for_date` or `get_fitness_summary`. It simply describes what it does, leaving the agent to infer usage context without any exclusions or alternative references.

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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