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gmail_not_important

Marks Gmail conversations as not important by row index, search query, label, or subject match, enabling AI agents to triage inboxes by selecting specific or all matching messages.

Instructions

Mark conversations as not important.

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

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not say whether the flag is reversible, whether it affects a single conversation or a batch, or what happens to the rows after the action — all relevant for a selection-based mutation tool.

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?

A single short sentence with no padding, and the action is front-loaded. It is efficient, though the terseness leaves the selection semantics entirely to the schema.

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

Completeness3/5

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

The schema fully documents the selection machinery and there is no output schema to explain, so an agent can technically call it. However, with no annotations and no statement of reversibility or scope, the description alone does not fully prepare the agent for a batch mutation.

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% and the seven selection parameters (all, index, indexes, match, query, folder, max_rows) are each documented in the schema. The description adds no meaning beyond that, so the baseline of 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?

States a specific verb and resource ('Mark conversations as not important'), which is unambiguous on its own. It does not explicitly contrast with the sibling gmail_important, though the inverse relationship is easy to infer from the names.

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?

There is no guidance on when to use this versus gmail_important, gmail_mark_read, gmail_archive, or gmail_trash. The agent is left to infer that this only toggles the importance flag rather than removing the conversation.

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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