Skill profile

greenlight

Pre-submission compliance scanner for the Apple App Store and Google Play.

What this skill does for you

Pre-submission compliance scanner for the Apple App Store and Google Play. Use this skill when reviewing iOS, macOS, tvOS, watchOS, visionOS, or Android app code (Swift, Objective-C, Kotlin, Java, React Native, Expo) to identify store rejection risks before submission, including Android manifest and Gradle policy checks and built APK/AAB inspection. Triggers on tasks involving app review preparation, compliance checking, App Store or Play submission readiness, target API level deadlines, restricted permissions, or when a user asks about App Store guidelines or Google Play Developer Program Policies.

Quoted from the skill description in the pinned source

Who made it

Publisherrevylai

Repositorygreenlight

Installs318as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the greenlight skill from revylai/greenlight.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: fcb36e395bd4ae20448f2535382baecba9396fd9. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: fcb36e395bd4ae20448f2535382baecba9396fd9. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: fcb36e395bd4ae20448f2535382baecba9396fd9. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/revylai/greenlight
Pinned skill file: View source at revision
Revision: fcb36e395bd4ae20448f2535382baecba9396fd9
Package hash: sha256:ed63ef50104ff4bd1da4e95141f093f4b76449b02d3920638bffbba494e0ada7
Licence: MIT