Skip to main content
Glama
anup-shesh

garmin-local-mcp

by anup-shesh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

circadian

Estimate your body clock's preferred wake time and bedtime from Garmin sleep history, and test the estimate against your own Garmin scores.

Instructions

Estimate when this user's body clock wants them to wake up, and test that estimate against their own Garmin history. Read-only: analyses synced sleep times locally and changes nothing.

Use for "am I a morning person?", "what time should I wake up?" or "what bedtime fits me?". For whether a single night or metric was normal, use baselines or get_day; for a relationship between two metrics, correlate.

Returns three separate estimates, each with an 80% interval: chronotype (MCTQ MSFsc, mid-sleep on free days corrected for catch-up sleep), sleep need, and an inferred wake window with bedtime. Also: stability across reasonable settings, and evidence from a rolling holdout on whether waking near the window went with higher Garmin scores beyond sleep duration and regularity (consistent / supportive / suggestive / unsupported; these describe consistency on unseen nights, not statistical significance), plus a plain-language interpretation and notes. Needs 28+ nights with sleep times; evidence needs 180+ days of history. Takes well under a second.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoLast wake date, YYYY-MM-DD. Default: yesterday.
startNoFirst wake date, YYYY-MM-DD. Default: 180 days before end.
detailNoAdd the wake-time bins, the sensitivity grid, per-fold model errors and bootstrap diagnostics (output up to about 6 KB).
outcomeNoGarmin score to test against: readiness_score, sleep_score or body_battery_high. Default: readiness_score, else sleep_score.
free_daysNoWeekdays whose mornings are alarm-free, as mon..sun. Default ["sat", "sun"]; use e.g. ["fri", "sat"] for a Friday-Saturday weekend.
sleep_need_minNoYour sleep need in minutes of time in bed, 240 to 720 (e.g. 480 for 8 h). Overrides the estimate from free-night sleep; useful when weekends are spent catching up.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.1.9
    • addedInput schema / properties / detail / description
      Added value: +"Add the wake-time bins, the sensitivity grid, per-fold model errors and bootstrap diagnostics (output up to about 6 KB)."
    • addedInput schema / properties / end / description
      Added value: +"Last wake date, YYYY-MM-DD. Default: yesterday."
    • addedInput schema / properties / free_days / description
      Added value: +"Weekdays whose mornings are alarm-free, as mon..sun. Default [\"sat\", \"sun\"]; use e.g. [\"fri\", \"sat\"] for a Friday-Saturday weekend."
    • addedInput schema / properties / outcome / description
      Added value: +"Garmin score to test against: readiness_score, sleep_score or body_battery_high. Default: readiness_score, else sleep_score."
    • addedInput schema / properties / sleep_need_min / description
      Added value: +"Your sleep need in minutes of time in bed, 240 to 720 (e.g. 480 for 8 h). Overrides the estimate from free-night sleep; useful when weekends are spent catching up."
    • addedInput schema / properties / start / description
      Added value: +"First wake date, YYYY-MM-DD. Default: 180 days before end."
  2. Addedv0.1.8

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does: it declares read-only behavior ('analyses synced sleep times locally and changes nothing'), data prerequisites (28+ nights, 180+ days for evidence), runtime (well under a second), and the semantics of the evidence labels (consistency on unseen nights, not statistical significance). This is well beyond what structured fields supply.

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-loads purpose, then routing, then returns, then requirements. Slightly long and the parenthetical acronym expansions (MCTQ MSFsc) add density, but nearly every sentence carries actionable information.

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?

No output schema and no annotations, yet the description fully describes the return structure (three estimates with 80% intervals, stability, holdout evidence with named confidence tiers, interpretation and notes) plus input requirements and runtime, so an agent has everything needed to call and interpret 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 description coverage is 100%, so all six parameters are already documented in the schema. The description explains the outputs (chronotype, sleep need, wake window) but adds no parameter syntax or default detail beyond what the schema provides. Baseline 3 applies.

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 and resource (estimate the user's body clock / wake time) and explicitly distinguishes itself from siblings: 'For whether a single night or metric was normal, use baselines or get_day; for a relationship between two metrics, correlate.' An agent can route without opening any 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 explicit trigger phrases ('am I a morning person?', 'what time should I wake up?') and names the alternative tools for adjacent questions. Clear when-to-use and when-not-to-use guidance.

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

Deploy Server

Other Tools