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List events

list_events
Read-onlyIdempotent

Retrieve calendar events across all connected Google accounts within a specified time range, labeled by source account, to answer schedule queries.

Instructions

List events in a time range. With no accounts argument this queries every account you may read and every visible calendar on them, which is what you want for questions like "what do I have tomorrow?". Each event is labelled with the account it came from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountsNoAccount ids to include. If omitted, every account you are permitted to read is included.
calendarNoCalendar id. Defaults to the account's configured default calendar ("primary" unless changed).
time_maxYesEnd of the range. A bare date means the end of that day.
time_minYesStart of the range. ISO 8601, e.g. "2026-09-20" or "2026-09-20T09:00:00".
timezoneNoIANA timezone for interpreting and displaying times, e.g. "Asia/Jakarta". Defaults to the server timezone.
max_resultsNoMaximum events per calendar. Default 250.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive, so the safety profile is covered. The description adds useful behavioral detail — that results are labelled with their source account and that omitting `accounts` fans out across all readable accounts — but says nothing about pagination, rate limits, or result ordering.

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 sentences, zero filler, with the broad-scope default and the concrete example front-loaded before the labeling note. Every sentence carries distinct information.

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 read-only listing tool with a fully documented schema and annotations covering safety, the description covers the key default-scope behavior and the account labelling of results. With no output schema, a brief note on return shape or ordering/pagination would round it out, but nothing critical for correct invocation is missing.

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 well documented, including the `accounts` omission default and the ISO 8601 / bare-date semantics of the time bounds. The description's restatement of the `accounts` default adds no syntax or format detail beyond the schema, so baseline 3 applies.

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 states a specific verb and resource ('List events in a time range') and clarifies the default scope when `accounts` is omitted, which is more than a restatement of the name. It does not, however, differentiate itself from close siblings such as `list_all_events` or `search_events`, leaving the agent to infer which listing tool applies.

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?

It gives a concrete usage context ('what do I have tomorrow?') and explains the condition under which the default broad query happens, which helps the agent decide on argument shape. It stops short of naming when to prefer an alternative such as `search_events` or `check_freebusy`.

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