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query_slow_rendering_rate

Query slow rendering rates for Android games to find the share of distinct users whose sessions missed target frame rates on over 25% of frames, with daily aggregation.

Instructions

Query the slow rendering rate of a game: slowRenderingRate20Fps and slowRenderingRate30Fps (share of distinct users whose sessions missed the target frame rate on more than 25% of frames) plus distinctUsers. Google only collects this for games — other apps get an error or empty rows. Ask for the *7dUserWeighted / *28dUserWeighted variants in metrics for rolling averages. Daily aggregation only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return (default: 50)
filterNoAIP-160 filter over dimensions, e.g. "versionCode = 415"
metricsNoMetrics to fetch (default: slowRenderingRate20Fps, slowRenderingRate30Fps, distinctUsers)
end_dateYesEnd date (inclusive) as YYYY-MM-DD, e.g. '2026-08-13'
dimensionsNoBreak the metrics down by these dimensions, e.g. ['versionCode','deviceModel']
start_dateYesStart date (inclusive) as YYYY-MM-DD, e.g. '2026-08-01'
package_nameNoApp package name, e.g. 'com.acme.app' (defaults to GOOGLE_PLAY_PACKAGE_NAME)
aggregation_periodNoAggregation granularity — this metric set only supports DAILY
Install Server

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses that non-game apps produce errors or empty rows and explains the metric semantics. However, it does not explicitly state that the operation is read-only or describe any potential side effects, though the query nature implies it.

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?

The description is concise yet information-dense, comprising two sentences that convey the core purpose, key metrics, usage restrictions, and parameter nuances. It avoids redundancy and stays focused.

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 description covers the essential context: what the tool does, when to use it (games only), metric definitions, rolling average variants, and aggregation period. It does not describe the output format, but given the query nature and sibling tools, this is acceptable. The description is sufficiently complete for a user to decide when and how to invoke it.

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?

The description adds value beyond the schema by explaining the meaning of the metrics (share of users missing frame rate thresholds) and clarifying the aggregation period limitation (only DAILY). It also hints at the need to request weighted variants in the metrics parameter, which the schema does not explicitly cover.

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 the tool's purpose: querying slow rendering rate metrics for games. It explicitly names the metrics (slowRenderingRate20Fps, slowRenderingRate30Fps) and provides a precise definition, distinguishing it from sibling query tools.

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?

The description gives explicit usage instructions: it is for games only and warns that other apps will yield errors or empty rows. It also advises using *7dUserWeighted / *28dUserWeighted variants for rolling averages and notes that only daily aggregation is supported, guiding the user on correct parameter usage.

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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