App stores
AuraScore 85/100

Cross-Platform Store Guideline Compliance and Rejection Risk Matrix

Map complex technical architectures against store guidelines to calculate rejection probabilities and mitigations.

Deploy this template prior to major releases or architectural refactors involving background processing, native bridging, or AI models. It yields an audit matrix identifying compliance friction points across platform review policies.

Template

Role: Principal App Store Compliance Architect & Regulatory Counsel

Context

  • Core App Architecture: {{application_architecture}}
  • High-Risk Permissions: {{permission_scopes}}
  • Third-Party Frameworks: {{integrated_sdks}}
  • Submission Target Window: {{target_release_timeline}}
  • Target App Store Ecosystems: {{store_guidelines_scope}}
  • Data Telemetry Profile: {{telemetry_policy}}

Task

Synthesize store review guidelines across ecosystems into an actionable technical compliance matrix, calculating rejection likelihood scores and code-level architectural mitigations for {{application_architecture}}.

Method

  1. Cross-reference {{permission_scopes}} against Apple App Review Guidelines (Section 5) and Google Play Policy Center (Data Safety).
  2. Deconstruct binary and runtime dependencies inside {{integrated_sdks}} to identify unapproved private API usage or tracking fingerprint risks.
  3. Formulate a risk score (1-100) based on historical rejection rates for {{telemetry_policy}} under current privacy manifest requirements.
  4. Analyze background processing hooks within {{application_architecture}} for policy adherence (e.g., background audio, location, VoIP exceptions).
  5. Map dynamic code loading or remote execution patterns against prohibition rules in {{store_guidelines_scope}}.
  6. Formulate fallback technical workarounds for each high-severity policy failure scenario.
  7. Compile findings into a structured compliance risk evaluation matrix.

Constraints

  • MUST cite exact guideline clause numbers (e.g., App Store Guideline 2.5.2, Google Play Declared Permissions Policy).
  • MUST compute a normalized Risk Priority Index (RPI = Severity x Detection Probability) for each entry.
  • MUST NOT recommend circumventing review processes; all mitigations must be policy-compliant engineering patterns.
  • Must provide concrete alternate APIs for any identified non-compliant framework.

Output format

  • Compliance Overview & Audit Scope (max 100 words)
  • Policy Risk Assessment Matrix (Markdown table with 6 columns: Feature/Module, Guideline Reference, Violation Risk Level, RPI Score, Technical Cause, Remediation Strategy)
  • Pre-Submission Reviewer Notes Script

Self-review

  • Confirm that all cited policies correspond accurately to {{store_guidelines_scope}}.
  • Validate that every RPI score is mathematically derived and bounded between 1 and 100.
  • Verify remediation patterns directly address the architectural constraints in {{application_architecture}}.
AuraScore breakdown
85/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

developers
developers-app-stores
complex-reasoning-analysis-math
compliance
app-review
privacy-manifest