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gmail_restore

Restore Gmail conversations to the Inbox from Trash, Spam, or archived mail. Select rows by index, subject match, search query, or folder, then move them back or add the Inbox label.

Instructions

Bring conversations back to the Inbox from the Trash, Spam or the archive (All mail / search).

Uses 'Move to Inbox' / 'Move to' -> Inbox when offered, else adds the Inbox label.

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

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the UI mechanism ('Move to Inbox' / 'Move to' -> Inbox when offered, else adds the Inbox label), which is useful, but omits permission requirements, whether the message is removed from Trash/Spam, and any side effects or reversibility.

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?

Two sentences, front-loaded with the core action and followed by a compact mechanism note. Every sentence contributes; the second sentence is slightly technical but not wasteful.

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 seven-parameter mutation tool with no annotations, the description plus a fully documented schema gives enough context to select and invoke it. It covers restore sources, destination, and fallback mechanism; only permission and side-effect details are left implicit, keeping it from a 5.

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 the schema already documents all seven parameters in detail. The description adds no parameter-specific semantics (e.g., how 'all', 'query', or 'match' interact), so the baseline of 3 is appropriate.

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 ('Bring conversations back') and destination (Inbox) with sources (Trash, Spam, archive/All mail), making the tool's purpose clear. It distinguishes itself in practice from siblings like gmail_archive or gmail_trash, though it does not explicitly name alternative tools.

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

Usage Guidelines3/5

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

The description implies the restoration scenario (from Trash/Spam/archive to Inbox) but gives no explicit 'use this when' or 'use X instead' guidance. It also omits prerequisites or when not to use it (e.g., for merely labeling a message), leaving usage to inference.

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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