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intervals-icu-mcp

by hhopke
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

icu_get_pace_curves

Read-onlyIdempotent

Fetch the pace-vs-duration curve to see sustained pace from 5s to 1h, revealing run/swim fitness trends and predicting race times; use GAP for hilly runs.

Instructions

Fetch the pace-vs-duration curve — best (fastest) sustained pace across durations from 5s up to 1h, aggregated over the chosen window.

Use for run/swim fitness trends and race-time predictions. Pass use_gap=True to normalize for hills via Grade-Adjusted Pace. For time-in-zone distribution within a single activity, use get_pace_histogram (or get_gap_histogram) instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
use_gapNoUse Grade Adjusted Pace (GAP) for running
days_backNoNumber of days to analyze (optional)
athlete_idNoAthlete ID (for coaches managing multiple athletes)
sport_typeNoSport type (e.g., Run, Swim)Run
time_periodNoTime period shorthand: 'week', 'month', 'year', 'all' (optional)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv5.0.1
    • addedInput schema / properties / athlete_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Athlete ID (for coaches managing multiple athletes)"
+}
  2. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real semantic behavior beyond that: the aggregation window, the 5s-to-1h duration span, and the fact that use_gap=True applies hill normalization via Grade-Adjusted Pace. It stops short of describing coverage limits or empty-data behavior, but the added context is substantive.

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?

Three compact sentences, front-loaded with the core definition, then the usage guidance, then the exclusion and alternative. Every sentence carries distinct information with no repetition of the schema.

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 five optional parameters all documented in the schema and an output schema present, the description is not obligated to describe return values. It supplies the metric definition, the when-to-use, the GAP nuance, and the sibling fallback — everything an agent needs to select and call it correctly.

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 baseline is 3, but the description explains the *purpose* of use_gap ('normalize for hills via Grade-Adjusted Pace') and clarifies what the curve's duration range means, adding meaning the bare schema text does not carry. It remains silent on the interplay of time_period vs days_back, which keeps it from a 5.

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 ('Fetch') and resource (pace-vs-duration curve), then defines the metric precisely: 'best (fastest) sustained pace across durations from 5s up to 1h, aggregated over the chosen window.' The alternative tool is named directly, so an agent can separate this from the histogram siblings 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?

Gives both positive and negative routing: 'Use for run/swim fitness trends and race-time predictions' and 'For time-in-zone distribution within a single activity, use get_pace_histogram (or get_gap_histogram) instead.' The condition that selects the alternative is explicit, and it even notes the use_gap variant to pass.

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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