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Python
Hybrid

google_ads_negative_placements_remove

Remove negative placement exclusions in batch by criterion ID, verifying each is a valid negative placement first. Revert a bad exclusions pass and return removed and skipped entries.

Instructions

Lifts delivery-surface exclusions by criterion_id, in one batch, so a bad exclusion pass can be reverted in a single call. Returns removed (criterion_id + resource_name), removed_count, and skipped entries with a reason. Mutating — lifting an exclusion lets the placement serve again from the next serving cycle. Ids are verified against the live criteria first: anything that is not a negative placement criterion at the named level is skipped, never removed. Get ids from google_ads_negative_placements_list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoWhy this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.
ad_group_idNoAd group ID for an ad group-level exclusion. Supply exactly one of campaign_id or ad_group_id. Ad group-level exclusions do not cascade to sibling ad groups.
campaign_idNoCampaign ID for a campaign-level exclusion. Supply exactly one of campaign_id or ad_group_id — the two are separate criteria and campaign-level exclusions apply to every ad group under the campaign.
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.
criterion_idsYesCriterion IDs to lift, as returned by google_ads_negative_placements_list or by the 'created' entries of google_ads_negative_placements_add. All must belong to the level named above.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.20.0
    • addedInput schema / properties / reason
      Added value: +{
+  "description": "Why this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.",
+  "maxLength": 500,
+  "type": "string"
+}
  2. Addedv0.10.44

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral burden: it states the mutating effect, when the change takes effect, batching, return shape, and the safety behavior of skipping non-negative criteria rather than removing them.

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?

Four dense sentences front-load the action and use case, then cover return values, mutation, validation, and id provenance. No filler or redundant restatement of the tool name.

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?

The tool is moderate in complexity and has no output schema, but the description supplies return values, mutation effects, and validation behavior. Mutual-exclusion and optional customer_id details are already in the schema, so nothing needed 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 coverage is 100% and the schema already explains criterion_ids, level exclusivity, customer_id fallback, and reason. The description adds useful confirmation that ids come from the list tool and that criterion_ids must belong to one level, but it does not substantially extend the schema's parameter documentation.

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?

The description opens with a specific verb and object: 'lifts delivery-surface exclusions by criterion_id, in one batch.' This clearly identifies the resource and operation, and it is readily distinguishable from sibling add/list 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?

It gives a concrete use case ('a bad exclusion pass can be reverted in a single call') and points to the list tool as the source of ids. It does not explicitly name when-not-to-use alternatives, but the delivery-surface/placement framing makes the boundary clear.

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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