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Google Play Console MCP

Search Error Issues

search_error_issues

Search grouped error issues to identify clusters of similar crashes and ANRs. Use filters for package, time window, and error type to diagnose stability problems.

Instructions

Search grouped error issues — clusters of similar crashes or ANRs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_byNoSort expression (e.g., 'errorReportCount desc')
days_backNoWindow size ending now, in days (default 7)
max_resultsNoMaximum number of issues to return (default 50)
package_nameYesApp package name (e.g., com.example.myapp)
filter_expressionNoOptional API filter (e.g., 'errorIssueType = CRASH')
sample_report_limitNoSample report names to attach per issue

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. 'Search' clearly signals a non-mutating read operation, and 'clusters' adds useful grouping context, but the description does not disclose limits, permissions, freshness, or any side-effect-free guarantee beyond what 'search' implies.

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?

A single, front-loaded sentence with no filler. It states the operation, the resource, and the key semantic distinction ('clusters') in a compact and efficient way.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The comprehensive input schema and output schema carry most operational detail, and the description adequately identifies the resource. However, with no annotations and no explicit guidance for choosing this tool over search_error_reports, the agent must infer selection context.

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 100%, and each parameter already has a meaningful explanation (e.g., order_by, days_back, filter_expression). The tool description adds no parameter-specific meaning, so the baseline of 3 is appropriate.

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 uses a specific verb ('Search') and resource ('grouped error issues'), and clarifies that these are clusters of similar crashes or ANRs. This helps distinguish it from the sibling search_error_reports, which targets individual error reports.

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 phrase 'clusters of similar crashes or ANRs' implies the agent should use this tool when it needs aggregated error issues rather than raw reports, but it never explicitly names an alternative or says when not to use it. Given the sibling search_error_reports exists, explicit routing guidance would have strengthened this dimension.

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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