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futureweb

Futureweb Intervals MCP

by futureweb

get_fueling_analysis

Read-only

Analyze carbohydrate, fluid, and sodium intake versus usage and sweat loss for one activity or a selected period.

Instructions

Use for carbohydrate, fluid and sodium intake of one activity (activity_id) or of the long sessions of a period (default the last 90 days, sessions of at least min_minutes; read-only).

Carbs used (Intervals.icu estimate) and ingested (logged total) in g and g/h, the ingested share of used, kcal and kJ, and fluid intake, sodium and sweat loss per hour where custom fields exist (found by units and name). One activity also gets the intake per hour from a custom intake stream, if there is one. Period: statistics per sport family, by duration and by intensity, Spearman correlations from 8 sessions, with sample sizes. Not logged is never 0; used minus ingested is no 1:1 energy deficit; no targets. Method: intervals://methods/fueling (get_guide).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoLast day YYYY-MM-DD (period mode); default today
athlete_idNoDefault: the configured athlete
start_dateNoFirst day YYYY-MM-DD (period mode); default 89 days before end_date; max 366 days
activity_idNoOne activity, e.g. i123456789; omit for the period mode
min_minutesNoMinimum moving time in minutes (period mode), not negative
sport_typesNoComma-separated activity types (period mode), e.g. "Ride,GravelRide"
detail_levelNoperiod: compact = per sport family; standard adds duration/IF buckets, correlations, 15 sessions; full lists all sessions. One activity: compact omits notesstandard
output_formatNojson = machine-readable, all fieldstext

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already cover readOnly, but the description adds substantial interpretive context: estimates vs logged intake, kcal/kJ handling, that correlations need 8+ sessions, and explicit caveats ('Not logged is never 0', 'used minus ingested is no 1:1 energy deficit', 'no targets'). It even points to the method guide via get_guide.

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 'Use for' purpose, then computation and caveat details. Dense and mostly earning its place, but some clauses are telegraphic fragments ('used minus ingested is no 1:1 energy deficit') that read run-on rather than trimmed.

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 an 8-parameter tool with no output schema, the description explains what the output contains (g and g/h, share of used, kcal/kJ, per-hour fluid/sodium/sweat loss, correlations with sample sizes) and the method behind them. Missing only a pointer to the closest sibling for differentiation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the per-parameter docs already carry baseline meaning. The description goes further by tying parameters together — activity_id selects single-activity mode, omitted triggers period mode with the 90-day default and min_minutes floor — and explains that detail_level omits notes in single-activity mode.

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 opening sentence names the exact resource (carbohydrate, fluid and sodium intake), both operating modes (one activity via activity_id vs period of long sessions), and the default scope. An agent can tell this apart from generic siblings like get_nutrition_summary by the fueling-specific content and the two-mode framing.

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?

'Use for ... intake of one activity (activity_id) or of the long sessions of a period' gives clear context and the condition that selects each mode. It stops short of naming alternatives (e.g. get_nutrition_summary) or stating when NOT to use it, so no full 5.

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