App stores
AuraScore 81/100

Humanitarian Aid App Store Metadata and Privacy Policy Validator

Creates a Python validation script to inspect store metadata, localized strings, and permission privacy compliance for NGO apps.

Use this template when preparing mobile applications for international aid and relief operations. It produces an executable Python CLI script that audits localized store descriptions and manifest permissions against strict privacy and data protection mandates.

Template

Role: Principal Humanitarian Mobile Compliance Engineer.

Context

  • NGO Program Name: {{ngo_program_name}}
  • Required Locales: {{target_locales}}
  • Distribution Platforms: {{store_platforms}}
  • Data Sensitivity Classification: {{data_sensitivity_tier}}
  • Privacy Policy Link: {{consent_policy_url}}
  • Whitelisted Permissions: {{allowed_device_permissions}}

Task

Author a standalone Python validation script that audits App Store and Google Play metadata directories, verifies localized privacy disclosures for {{target_locales}}, and checks native manifest permissions against {{allowed_device_permissions}} for {{ngo_program_name}}.

Method

  1. Define configuration data structures incorporating {{data_sensitivity_tier}} rules and accepted values.
  2. Write metadata parsing logic to traverse localized store assets (description, keywords, privacy URLs) for all entries in {{target_locales}}.
  3. Implement regex and HTTP verification checks ensuring {{consent_policy_url}} resolves and contains required non-profit data protection clauses.
  4. Build native manifest parsers (AndroidManifest.xml and Info.plist) to scan all requested hardware and runtime permissions.
  5. Compare extracted permissions against {{allowed_device_permissions}}, flagging any unapproved location, contact, or telemetry access.
  6. Generate structured compliance scoring tailored to {{store_platforms}} requirements.
  7. Add CLI arguments (argparse), structured exit codes (0 for pass, 1 for fail), and automated markdown report emission.
  8. Embed clear remediation suggestions in the terminal output for any failing check.

Constraints

  • MUST be written in standard Python 3.10+ using only standard library modules to ensure zero-dependency CI execution.
  • MUST NOT permit builds to pass if undeclared permissions outside {{allowed_device_permissions}} are detected.
  • The script must validate URL reachability using non-blocking connection timeouts.
  • Error outputs must highlight exact file paths and line mismatches.

Output format

  1. Script Overview and Dependencies
  2. Complete Executable Python Script (validate_store_compliance.py)
  3. Sample Configuration File (store_compliance.json)
  4. Integration Instructions for Pre-commit and CI Pipelines

Self-review

  • Ensure all variables (including {{ngo_program_name}} and {{consent_policy_url}}) are properly bound within the script logic.
  • Verify standard library compliance (no unlisted pip packages required).
  • Check that both iOS Info.plist and Android AndroidManifest.xml validation paths are fully implemented.
AuraScore breakdown
81/100Provisional
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 efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

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
public-sector-nonprofit
python
ngo
privacy-compliance