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gmail_mute

Mute selected Gmail conversations so they are archived and future replies skip the Inbox; locate muted threads later with the is:muted search.

Instructions

Mute conversations: they are archived and later replies skip the Inbox (find them with 'is:muted').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allNoAct on EVERY conversation of the query/folder list (Gmail's 'Select all' after loading the whole list; repeated until the list is empty for actions that remove conversations from it). Needs query or folder; no index/indexes/match.
indexNoRow index from gmail.list / gmail.search (0 = first row).
matchNoSelect every row whose subject contains this text (case-insensitive).
queryNoRun this Gmail search first and take the rows from its results.
folderNoOpen this folder/label first and take the rows from it.
indexesNoSeveral row indexes (multi-selection).
max_rowsNoWith match, look at most at this many rows from the top.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does disclose the key effects: conversations are archived, future replies bypass the Inbox, and they can be found with 'is:muted'. It stops short of mentioning reversibility via gmail_unmute or any permission prerequisites, but the core mute behavior is well explained.

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 definition is a single front-loaded sentence that states the action and its most important consequences without filler. Every clause earns its place by clarifying what mute means in Gmail terms.

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 tool with seven selection parameters but complete schema coverage, the description sufficiently explains the mute effect and how to locate muted conversations. It lacks usage guidance relative to alternatives and does not mention reversibility, but an agent has enough information to understand the operation and use the documented selection parameters.

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 every parameter is already documented in the input schema, including selection modes like all, index, query, folder, and match. The description adds no parameter-specific meaning beyond calling the target 'conversations', 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 ('Mute conversations') and explains the core effect: archived messages and future replies skipping the Inbox. It clearly identifies the action, though it does not explicitly distinguish it from nearby siblings such as gmail_archive or gmail_snooze.

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 explains what muting does but not when to choose it over alternatives like gmail_archive, gmail_snooze, or gmail_label. There are no explicit when-to-use or when-not-to-use conditions, leaving selection guidance to inference from the tool name and effect.

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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