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Google Play Store Policy Advisor

android_play_policy_advisor
Read-only

Advises on Google Play Store policy requirements for October 2025 changes, including restricted permissions, subscription transparency, and large-screen quality tiers to avoid review failures.

Instructions

Play Store policy reference — October 2025 changes and ongoing requirements. AI tools have zero awareness of these policy changes. Review failures cost weeks of re-submission. Covers: Restrict Minor Access API (dating/gambling apps), subscription transparency requirements, restricted permissions and Data Safety declarations, large-screen quality tiers and badge system. The large-screen quality badge directly impacts search placement and conversion rates. Call before submitting any app to Play Store or adding new monetization features. Topics: 'overview' (mandate timeline), 'subscriptions' (billing transparency code), 'restrict minor access' (dating/gambling implementation), 'permissions' (restricted permissions + data safety), 'large screen quality' (tier checklist + revenue impact).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoTopic: 'overview', 'subscriptions', 'restrict minor access', 'permissions', 'large screen quality'
Behavior4/5

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

Annotations declare readOnlyHint=true, which matches the description's reference nature. The description adds context about AI unawareness of policy changes and consequences (weeks of re-submission), which exceeds what annotations provide.

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 a clear overview, specific topics, and usage instruction. It is longer than minimal but every sentence adds value, including caveats about AI awareness and real-world impact.

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?

For a policy reference tool with one parameter and no output schema, the description adequately explains its purpose, topics, and use cases. It could briefly mention the response format, but overall it is complete.

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?

Schema covers 100% of parameters with a description for 'topic' listing allowed values. The description adds semantic context for each topic (e.g., 'mandate timeline' for overview, 'billing transparency code' for subscriptions), enriching the schema's information.

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 identifies the tool as a Play Store policy reference covering October 2025 changes and ongoing requirements. It lists specific topics (e.g., Restrict Minor Access API, subscription transparency) and distinguishes from sibling tools like android_permission_advisor or android_large_screen_guide by focusing on policy compliance and submission

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 explicitly states 'Call before submitting any app to Play Store or adding new monetization features,' providing clear context for when to use. It does not list exclusions or alternatives, but the sibling list implies differentiation.

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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