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Set Reminder

set_reminder

Schedules a one-time spoken reminder: at the given time the room's Sonos speaker reads the text aloud (text-to-speech). Takes either at (the home's local time, 24-hour HH:MM) or in_minutes. Examples: {text:'Time to get up',room:'Bedroom',at:'07:30'} / {text:'焗炉好了',room:'客厅',in_minutes:20}. This is ZoneFoundry's own scheduler, separate from native Sonos alarms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
atNoLocal time in the home's own time zone, 24-hour HH:MM (e.g. '08:00', '20:30'); Chinese phrases like '明早7点半' also work; past times roll to tomorrow
roomYesRoom name as shown in the Sonos app (usually English, e.g. "Living Room"). Common Chinese aliases (客厅/主卧) also resolve. Omit for the default room.
textYesWhat the speaker should say at fire time
languageNo
in_minutesNoFire after N minutes (takes precedence over `at`)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark it as a mutating but non-destructive operation. The description adds behavior beyond that: the reminder fires once, the speaker reads the text aloud, and scheduling is ZoneFoundry-specific. No hidden destructive effects are indicated, and the description does not contradict the annotations.

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 short sentences plus two concrete JSON examples carry the whole message without repeating the title or schema. The most important purpose statement comes first, and the final distinguishing note is short.

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 a 5-parameter scheduling tool with no output schema, the description is near-sufficient: purpose, time formats, examples, and differentiation are covered. It does not mention return/confirmation behavior or explicitly require one of `at`/`in_minutes`, but the schema and examples make successful invocation likely.

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 high (80%), so the baseline is 3; the description's examples and the `at` vs `in_minutes` relationship add modest clarity. It does not improve on the schema's explanations for `text`, `room`, or `language`, and it leaves the 'at least one time parameter' requirement slightly ambiguous.

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 definition states a specific action ('Schedules a one-time spoken reminder') with a clear resource (the room's Sonos speaker reading text aloud). It also disambiguates from native Sonos alarms by noting this is ZoneFoundry's own scheduler, so it stands apart from generic reminder tools.

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?

The context for use is clear: future one-time spoken reminders, with either an absolute time or a relative delay. It separates itself from native Sonos alarms but does not explicitly point to sibling tools like cancel_reminder/list_reminders or announce for alternative cases, so it stops short of full when/when-not guidance.

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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