ReminderIt

Edit reminder

update_reminder

DestructiveIdempotent

Edit a reminder's wording or schedule. Only the fields you pass are changed.

Use for "move it to 7am", "say it differently", "stop after the 20th". To pause or
resume, use pause_reminder / resume_reminder. To change the voice, use
set_reminder_voice. To skip particular dates, use set_skip_dates.

Args:
    reminder_id: Reminder to edit (from list_reminders).
    title: New short label.
    message_text: New spoken message (written as natural speech, max 600 chars).
    cron_expr: New cron schedule, e.g. "0 7 * * *" for daily 7am.
    interval_days: New "every N days" interval (1-365).
    run_at: New ISO 8601 datetime for a one-off reminder.
    timezone: New IANA timezone. Changing this moves every future call.
    start_date: New ISO start date for a recurring series.
    end_date: New ISO end date; the series stops after it.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "reminder_id": "<reminder_id>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "update_reminder"
  }
}

Input Schema

Name	Required	Description
`title`	No
`run_at`	No
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`end_date`	No
`timezone`	No
`cron_expr`	No
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`start_date`	No
`reminder_id`	Yes
`message_text`	No
`interval_days`	No
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

Name	Required	Description	Default
`result`	Yes
`_mcp_instructions`	No	Server-issued metadata for this conversation.

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedOct 27, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "reminder_id"
-]New value: +[
+  "reminder_id",
+  "context",
+  "llm_model"
+]

addedOutput schema / properties / _mcp_instructions

Added value: +{
+  "description": "Server-issued metadata for this conversation.",
+  "properties": {
+    "conversation_id": {
+      "description": "The server-issued conversation identifier.",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedSep 30, 2026

TDQS

A4.5/5.0

Behavior4/5

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

"Only the fields you pass are changed" is genuine partial-update semantics not conveyed by the annotations, and "Changing this moves every future call" discloses a real side effect of timezone edits. However, for a tool annotated destructiveHint=true, the description never says what is lost or overwritten when a new schedule replaces an existing one (e.g. whether cron_expr wipes interval_days), leaving the destructive behavior undisclosed.

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-loaded with purpose and the partial-update rule, then a routing sentence, then an args list that adds semantics rather than restating schema titles. The arg block is slightly long, but almost every line earns its place.

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 12-parameter mutation tool with an output schema and annotations carrying the safety profile, this covers purpose, alternatives, partial-update behavior, and per-field formats. The missing piece is scheduling-field mutual exclusivity and the concrete consequence of a destructive schedule overwrite.

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?

With only 25% schema coverage, the description carries the load and mostly does: it supplies a cron example, the 1-365 range for interval_days, the 600-char limit and speech style for message_text, and format hints (ISO 8601, IANA) for the date/timezone fields. The gap is that it never states whether cron_expr, interval_days, and run_at are mutually exclusive or how they interact.

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 ("Edit a reminder's wording or schedule") and immediately names the sibling tools it is not (pause_reminder, resume_reminder, set_reminder_voice, set_skip_dates). An agent can route correctly 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 concrete trigger utterances ("move it to 7am", "say it differently") and explicit alternative tools with the condition that selects each. Both when-to-use and when-to-use-something-else are covered.

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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