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johnoconnor0

Google Ads MCP Server

by johnoconnor0

google_ads_budget_pacing

Analyze campaign budget pacing and spending velocity to identify overpacing or underpacing, with projected month-end spend and recommendations for budget adjustments.

Instructions

Analyze budget pacing and spending velocity for a campaign.

Shows:

  • Current spend vs. expected spend

  • Pacing percentage (overpacing, underpacing, on track)

  • Projected month-end spend

  • Days remaining in the month

  • Recommendations for budget adjustments

Args: customer_id: Google Ads customer ID (10 digits, no hyphens) campaign_id: Campaign ID to analyze

Returns: Budget pacing analysis with recommendations

Example: google_ads_budget_pacing( customer_id="1234567890", campaign_id="12345678" )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
campaign_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It uses 'Analyze' which suggests a read operation, but does not explicitly state that no changes are made or mention any side effects, rate limits, or permissions. Adequate but could be clearer.

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?

The description is well-structured with sections for summary, outputs, arguments, return, and example. It is concise but some bullet points could be integrated into prose for brevity.

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?

The tool's complexity is moderate, and the description covers key outputs, parameter formats, and a usage example. The existence of an output schema helps, but the description still provides necessary context for initial understanding.

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

Parameters4/5

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

Despite 0% schema description coverage, the description provides detailed parameter explanations (e.g., '10 digits, no hyphens' for customer_id) and an example call, adding significant value over the schema.

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 clearly states 'Analyze budget pacing and spending velocity for a campaign' and lists specific outputs (current spend, pacing percentage, etc.), distinguishing it from siblings like budget_recommendations or performance_forecaster.

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

Usage Guidelines3/5

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

The description implies usage for analyzing pacing but does not explicitly state when to use this tool vs alternatives like budget_recommendations or wasted_spend_analysis. No when-not-to-use or prerequisite info is provided.

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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