AdCopilot

Google Ads: remove negative keywords

remove_negative_keywords

DestructiveIdempotent

Takes negative keywords back out of a campaign.

The inverse of add_negative_keywords: pass the same keywords (text and
match type). The campaign can show for those searches again at once,
which can raise what a running campaign spends. Only the campaign's
negative keywords are looked at: a keyword it bids on, an excluded
location or any other setting is never changed.

Text is matched ignoring case and extra spaces, and the match type must
match too. A keyword the campaign does not have as a negative is
reported in not_found and nothing is done for it; when none is found,
nothing is sent.

Args:
    customer_id: The Google Ads customer ID (numbers only, no hyphens).
    campaign_id: The ID of the campaign (digits only).
    keywords: List of keyword objects, each with:
        - text: The keyword text (e.g., "free LMS").
        - match_type: One of: EXACT, PHRASE, BROAD. Default: BROAD,
          as in add_negative_keywords.

Returns:
    Dictionary with removed (text, match_type and resource_name of each
    negative keyword taken out), not_found (each keyword the campaign
    did not have) and keywords_removed.

Tools revision: 5c9bea8f.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`keywords`	Yes
`campaign_id`	Yes
`customer_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Adds substantial behavior beyond annotations: removal can immediately raise spend, matching is case/space-insensitive and match-type-sensitive, unmatched keywords are reported in not_found, and no request is sent if none match. These details make the destructive and idempotent annotation hints actionable.

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?

Front-loads purpose, then uses clear Args/Returns structure. Despite its length, each section serves parameter clarification or mutation behavior; there is no filler.

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

Completeness5/5

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

For a destructive partial-failure mutation, it covers scope, side effects, matching rules, not_found handling, and return fields. With annotations and an output schema also present, an agent has enough information to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully documents all three parameters: customer_id format, campaign_id digits-only, and keywords objects with text plus match_type enum/default. This compensates for the absent schema descriptions.

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 mutation ('Takes negative keywords back out of a campaign') and identifies itself as the inverse of add_negative_keywords. It also scopes the operation to campaign negative keywords and explicitly excludes bid keywords, excluded locations, and other settings, making it distinguishable from broader removal tools.

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?

Frames typical use as undoing add_negative_keywords by passing the same text and match type, and warns about spend impact. It clearly scopes to campaign negatives, but does not explicitly route the agent to remove_from_negative_keyword_list or remove_account_negatives instead, leaving that alternative selection partly inferential.

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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