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AdsAgent — Google Ads MCP

google_ads_negative_location_add_prepare

Prepare to exclude a geographic target from a campaign. Saves a private draft after Google validate-only and a complete affected-resource snapshot; does not send the change. Show the draft for explicit approval before calling google_ads_negative_location_add_confirm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
customer_idYes10-digit Google Ads customer id.
connection_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / connection_context
      Added value: +{
      +  "pattern": "^mctx_v1_[0-9a-f]{64}$",
      +  "type": "string"
      +}
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (destructiveHint=false, openWorldHint=false), and the description adds real context beyond them: it saves a private draft, runs a Google validate-only pass, captures a complete affected-resource snapshot, and does not transmit any change. This is exactly the kind of mutation-semantics disclosure the annotations cannot express.

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?

Three sentences, zero filler, front-loaded with purpose then behavior then next-step. Each sentence carries distinct information an agent needs.

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?

No output schema exists, and the description does communicate that a draft is produced and should be surfaced for approval, which is the key return expectation. It stops short of explaining draft retrieval/expiry or how geo_target_id should be obtained (e.g. via google_ads_geo_targets_suggest), leaving minor gaps for a two-phase mutation tool.

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 low (33%) – only customer_id is documented, and the nested body fields (campaign_id, geo_target_id) plus connection_context have no schema descriptions. The description partially compensates by mapping the two body fields to their conceptual roles ('exclude a geographic target from a campaign'), but gives no format, sourcing, or connection_context guidance.

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?

Specific verb and resource: 'Prepare to exclude a geographic target from a campaign.' It immediately distinguishes itself from its sibling by noting it does not send the change and that google_ads_negative_location_add_confirm is the follow-up. An agent can route correctly without opening either schema.

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

Usage Guidelines5/5

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

Explicitly states the workflow: this is the prepare step, show the draft for explicit approval, then call google_ads_negative_location_add_confirm. The alternative tool and the condition that selects it are named directly.

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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