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Futureweb Intervals MCP

by futureweb

get_wellness_trends

Read-only

Read multi-day trends for chosen wellness metrics against the athlete's own baseline, with rolling means, statistics and optional correlations (not causes).

Instructions

Use for multi-day wellness trends against the athlete's own baseline (default the 42 days ending today; read-only, statistics only).

Per metric with units: the daily values of the last 14 days with trailing means, period statistics, a personal baseline (the 42 days ending at end_date), the latest value vs that baseline (difference, %, z-score), rolling means, the last 7 days vs the 7 before and outliers (|z| >= 2.5). Missing days are never filled in; for physiological metrics a stored 0 counts as missing. Small samples are flagged (baseline under 14 values, correlation under 30 paired days). Weight adds a 7/14/28-day slope in kg per week. Optional correlations (Pearson, Spearman, with lag) are associations, not causes. One day in context: get_recovery_snapshot. Method: intervals://methods/wellness (get_guide).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricsNoComma-separated, at most 16: native codes (hrv, restingHR, weight, ctl ...), custom field codes, eftp_<Type>hrv,restingHR,avgSleepingHR,sleepScore,readiness,respiration,spO2,weight
windowsNoComma-separated rolling windows in days, 2-3657,14,42
end_dateNoLast day YYYY-MM-DD; default today
athlete_idNoDefault: the configured athlete
start_dateNoFirst day YYYY-MM-DD; default 41 days before end_date (42 days)
correlationsNoComma-separated pairs "a:b" or "a:b:lag_days" (b lag days later), e.g. "hrv:readiness,restingHR:sleepScore:1"
output_formatNojson = machine-readable, all fieldstext

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, yet the description adds substantial behavior: missing days are never filled, stored 0 counts as missing for physiological metrics, small samples are flagged, correlations are associations not causes, and weight adds a 7/14/28-day slope. These are non-obvious data-handling rules an agent needs to interpret results correctly.

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?

Dense and front-loaded: purpose first, then per-metric output shape, then caveats, then the sibling pointer and method link. It is long, but with no output schema the return-value detail earns its place; only minor tightening is possible.

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?

With no output schema, the description fully carries the return-value burden: it enumerates per-metric fields (trailing means, z-scores, rolling means, outliers, slope), flags small-sample conditions, and notes the method guide. An agent has everything needed to interpret and call it.

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 coverage is 100%, documenting every parameter including the 'a:b:lag_days' correlation syntax and the metrics code list, so the schema does the heavy lifting. The description explains output semantics rather than adding parameter syntax beyond the schema, which is the expected baseline 3.

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+resource ('multi-day wellness trends') with explicit scope ('against the athlete's own baseline, 42 days ending today'). It explicitly routes the agent away from the single-day sibling ('One day in context: get_recovery_snapshot'), making it distinguishable without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Front-loads 'Use for...' and then names the alternative tool and the condition that selects it ('One day in context: get_recovery_snapshot'). The statistics-only, read-only framing further delimits when this tool applies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.