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kLOsk

Google Ads - AdLoop

by kLOsk

run_ga4_report

Read-only

Execute custom GA4 reports by specifying dimensions, metrics, and date ranges to analyze website or app performance.

Instructions

Run a custom GA4 report with specified dimensions, metrics, and date range.

Common dimensions: date, pagePath, sessionSource, sessionMedium, country, deviceCategory, eventName Common metrics: sessions, totalUsers, newUsers, screenPageViews, conversions, eventCount, bounceRate

Date formats: "today", "yesterday", "7daysAgo", "28daysAgo", "90daysAgo", or "YYYY-MM-DD". If property_id is empty, uses the default from config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dimensionsNo
metricsNo
date_range_startNo7daysAgo
date_range_endNotoday
property_idNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate read-only and non-destructive behavior. The description adds that the report is custom and explains default property_id usage, providing useful behavioral context beyond annotations.

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 concise with two sentences and bullet-like lists for dimensions, metrics, and date formats. It is front-loaded with the main action. Could be slightly more organized but is not verbose.

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?

Given the optional parameters and output schema present, the description provides sufficient context to use the tool. It lists common inputs but lacks details on output structure, though the output schema covers that.

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 0%, so the description must compensate. It offers common dimensions/metrics and date formats but does not explain each parameter's role (e.g., limit, or that all parameters are optional). The added value is moderate.

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 it runs a custom GA4 report with specified dimensions, metrics, and date range. It lists common dimensions and metrics, establishing it as specific to GA4 reporting, which distinguishes it from siblings like run_realtime_report or run_gaql.

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?

The description provides guidance on date formats and default property_id behavior, implying usage context. However, it does not explicitly state when not to use this tool or compare with siblings like run_realtime_report for real-time needs.

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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