Skip to main content
Glama
sikcapri

SuperGlookoQuery

by sikcapri
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
JavaScript
Local

Basal delivery state timeline

get_basal_delivery
Read-only

Retrieve the Omnipod-5 basal delivery state timeline (normal, suspend, max, limited) to investigate lows, rebound patterns, and limited-mode periods.

Instructions

What the pump's automated-delivery algorithm was doing with basal over time: delivering normally, pausing it (suspend), running at its ceiling (max), or running blind on a fixed preset because it lost CGM signal (limited).

DEVICE COVERAGE: this reads an Omnipod-5-specific Glooko data series. Confirmed empty (never populated) for a CamAPS FX account, likely the same for other non-Omnipod pumps — an empty result means this view genuinely isn't available for that device, NOT that basal ran normally throughout; never present the absence of data as a normal reading. For a CamAPS FX account, get_camaps_pump_mode_breakdown's automatic/manual/ easeOff/boost/liberty/attempting percentages are the nearest available picture of algorithm behaviour, though not a like-for-like replacement for this state timeline.

IMPORTANT: these are STATES describing the algorithm's behaviour, NOT insulin amounts. "suspend" means paused, "max" means at the ceiling; neither is a number of units. (For basal units, use get_daily_insulin.)

Use it to investigate lows (was basal already suspended beforehand?), rebound patterns (max, then suspend, then a low), how hard the system is working, and whether excursions coincided with limited mode (algorithm not adjusting at all).

Times are plain wall clock time (device-local), not UTC. Capped to a generous span since it returns collapsed intervals, not raw points.

Returns: a summary of minutes and percentage per state (normal/suspend/max/limited) and, unless includeIntervals is false, an intervals array (state, start, end, minutes).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYesRequired. Window end as an ISO 8601 timestamp, e.g. 2026-06-20T00:00:00.000Z — plain wall clock time, same caveat as start (the "Z" is a format artifact, not a UTC claim). Treated as inclusive and must be after start. All timestamps returned by this API are likewise plain wall clock time, unconverted.
startYesRequired. Window start as an ISO 8601 timestamp, e.g. 2026-06-19T00:00:00.000Z. IMPORTANT: despite the trailing "Z", this is plain WALL CLOCK time, not true UTC — Glooko records only the literal date/time the patient's device showed, with no timezone attached. Use the patient's own wall-clock digits directly (no conversion): resolve "yesterday" or "last 3 weeks" straight into the matching wall-clock date and time. Treated as inclusive.
includeIntervalsNoOptional (default: true). Whether to include the full interval timeline. Set false to get only the per-state summary totals, which is much smaller over a long span.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses substantial behavioral context: state meanings, device-specific data availability, the empty-result caveat, plain wall-clock time semantics, a capped span due to collapsed intervals, and the exact shape of the return value. This goes well beyond what annotations provide and contains no contradiction.

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?

The description is long but every paragraph earns its place: core definition, device coverage, key distinction from insulin amounts, use cases, time semantics, and return shape. It is front-loaded with the central concept and uses structure and emphasis to keep important caveats scannable. No redundant 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 that there is no output schema, the description thoroughly compensates by explaining exactly what will be returned: per-state minutes/percentages and an intervals array with state, start, end, and minutes. It also covers crucial edge cases such as empty results for unsupported devices, the non-UTC time caveat, and the difference between states and units. Nothing essential is missing for correct invocation.

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 the input schema already documents start, end, and includeIntervals in detail. The description reinforces the wall-clock caveat and mention of includeIntervals, but it does not add significant parameter-level meaning beyond what the schema provides. A baseline 3 is appropriate.

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 the tool's purpose with a specific subject ('the pump's automated-delivery algorithm'), resource ('basal over time'), and a precise set of states (normal, suspend, max, limited). It also explicitly differentiates itself from get_daily_insulin by clarifying these are states, not insulin amounts, leaving no ambiguity about what the tool does.

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?

It provides explicit use cases ('investigate lows', 'rebound patterns', 'how hard the system is working', 'whether excursions coincided with limited mode'), a direct alternative for basal units ('use get_daily_insulin'), and warns against treating empty results as normal for non-Omnipod devices. This is strong 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.

Install Server

Other Tools