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google-ecommerce-mcp

Plan: add Google Ads negative keywords

gads_plan_add_negatives
Read-only

Plan adding 1–50 EXACT, PHRASE, or BROAD negative keywords to a campaign or shared negative list in one atomic dry-run request; negatives only stop ads from showing.

Instructions

Plan adding negative keywords (1 to 50 texts given by you, match type EXACT, PHRASE or BROAD) to one campaign (campaign_id) or to one shared negative keyword list (shared_set_id), in one atomic request, dry-run by Google first. Negatives only stop ads from showing (no spend increase). Rollback is manual (remove them in the interface).

Input Schema

NameRequiredDescriptionDefault
keywordsYesNegative keyword texts (1 to 50, at most 10 words each)
client_idNoClient id from clients_list; empty uses the only client
match_typeNoMatch type of every negativeEXACT
campaign_idNoCampaign id
customer_idNoGoogle Ads customer id (10 digits, dashes allowed); empty uses the client's own customer
shared_set_idNoShared negative keyword list id (shared_set.id); or give campaign_id

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A4.1/5.0
Behavior4/5

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

Adds real operational context beyond annotations: the request is atomic, Google dry-runs it first, negatives can only suppress delivery (no spend risk), and rollback is manual. Annotations already cover read-only/non-destructive status, so the remaining gap (what the plan artifact looks like, how it is later applied) is minor.

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?

Three tight sentences with the action and targets front-loaded; the parenthetical restating the 1-50 limit and match types duplicates the schema slightly but is compact. No filler or hedging.

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?

Covers target selection, limits, atomicity, the dry-run behavior, risk profile, and rollback for a six-parameter mutation-planning tool with no output schema. It does not describe the plan output/next step, which is the only notable omission.

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%, so the schema already documents keywords, match_type, client_id, customer_id, campaign_id, and shared_set_id. The description echoes the keyword count, match types, and target selector but adds only the campaign-vs-shared-set exclusivity nuance, which the schema also hints at.

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 verb (add), resource (negative keywords), and scope (to a campaign or a shared negative keyword list) in one atomic request. It is immediately distinguishable from siblings such as gads_plan_pause_entities or gads_plan_create_campaign without opening any schema.

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?

Clearly explains the two targeting modes (campaign_id or shared_set_id) and signals that this is a Google-side dry-run plan whose rollback is manual removal in the interface. It stops short of naming the execution step (applying the plan, e.g. via gads_apply) or quantifying when to prefer this over other gads_plan_* tools.

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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