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Trend of one metric

metric_trend
Read-only

Determine the slope and fit quality of a WHOOP metric like recovery, HRV, sleep, or strain across a date range, with rolling means for trend analysis.

Instructions

Compute the direction and rate of change of one metric over a range.

Args: metric: One of "recovery_score", "hrv", "resting_heart_rate", "sleep_performance", "sleep_efficiency", "strain". start: ISO 8601 start of the range. end: ISO 8601 end of the range.

Returns the least-squares slope in metric units per day. A slope is a description of the window requested, not a forecast. Also returns an r² fit-quality figure for that slope -- both as the number and as a word ("strong"/"moderate"/"weak"/"negligible") -- and 7/30/90-day rolling means of the metric over calendar days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYes
startYes
metricYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With annotations declaring readOnlyHint=true, the safety profile is already known. The description adds valuable context that the slope is 'a description of the window requested, not a forecast' and discloses the return of r² and rolling means, which helps set expectations beyond the schema.

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?

The description is well-structured with clear sections (Args, Returns) and the purpose is front-loaded. It is slightly longer than minimal but every sentence carries substantive information—no filler.

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 presence of an output schema, the description need not detail every return field, but it does describe the key outputs (slope, r², rolling means) and provides an important interpretation caveat. All parameters are fully explained, and the tool's purpose is unambiguous, making it complete for an agent.

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?

The Args section in the description fully documents all three parameters—metric (with explicit enum-like options), start, and end (with ISO 8601 format). This completely compensates for the schema's generic string types, providing rich meaning beyond the input schema.

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 clearly states 'Compute the direction and rate of change of one metric over a range,' using a specific verb and resource. It distinguishes itself from siblings by focusing on single-metric trend analysis rather than correlation or period comparison.

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 gives clear context for when to use this tool—when you need a trend (slope) of one metric over a time range. It does not explicitly mention alternatives or exclusion criteria, but the 'not a forecast' caveat adds a boundary for interpretation.

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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