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Krishna-Desiraju

Apple Reminders MCP Server

create_reminder

Create new reminders in Apple Reminders with customizable attributes including due dates, priorities, tags, and notes to help users organize tasks and manage their schedule.

Instructions

Create a new reminder in Apple Reminders with comprehensive attributes

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesThe reminder title/name (required)
notesNoAdditional notes or description for the reminder
listNameNoName of the list to add reminder to (defaults to default list)
dueDateNoDue date in ISO 8601 format (e.g., "2024-12-31T14:00:00Z")
priorityNoPriority: 0=none, 1=high/urgent (!!!), 5=medium, 9=low
tagsNoArray of tag names to apply (encoded as [#tag] in notes)
flaggedNoWhether to flag this reminder
urlNoURL to associate with the reminder
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a reminder but doesn't cover aspects like whether it requires specific permissions, how errors are handled, what the return value looks like, or any rate limits. This is a significant gap for a mutation tool with zero annotation coverage.

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?

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, though it could be slightly more specific (e.g., noting it's for Apple Reminders only). Every word earns its place, but it's not maximally dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a creation tool with 8 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context, usage guidelines, and details on the return value, leaving significant gaps for an AI agent to understand how to invoke it correctly beyond basic parameter input.

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?

The schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between parameters or default behaviors. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('create a new reminder') and specifies the target system ('in Apple Reminders'), which distinguishes it from generic creation tools. However, it doesn't explicitly differentiate from sibling tools like 'update_reminder' beyond the verb 'create' versus 'update'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'update_reminder' or 'complete_reminder', nor does it mention prerequisites such as authentication or list availability. It lacks explicit usage context or exclusions.

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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