Levyra Android Reverse Engineering
SkillMonitoring & opsMandatory Levyra workflow for lawful Android artifact decompilation, APK/XAPK/AAB/DEX/JAR/AAR analysis, API extraction, compiled call-flow tracing, obfuscation analysis, and authorized dynamic diagnostics.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Levyra Android Reverse Engineering skill
What this skill tells your AI
The instructions your AI receives, as published by luc4n3x/levyra-deepsound in .agents/skills/levyra-android-reverse-engineering/SKILL.md and read by ahel’s review.
Use this skill whenever the task analyzes compiled Android artifacts rather than Levyra source directly: APK, XAPK, AAB, DEX, JAR, AAR, jadx/smali output, compiled API extraction, binary call-flow tracing, or Kotlin/R8 metadata recovery.
This is the cross-runtime canonical adapter. Claude Code may additionally use the
approved SimoneAvogadro/android-reverse-engineering-skill plugin. Do not load a
second upstream plugin exposing the same android-reverse-engineering skill or
/decompile command in parallel.
Upstream basis
The preferred Claude upstream is SimoneAvogadro/android-reverse-engineering-skill
because its workflow is especially strong for native Kotlin/KMP, fingerprint-first
triage, R8-resistant Kotlin-name recovery, Ktor/Apollo/Koin extraction, split APKs,
and Windows/PowerShell operation.
Useful static-analysis ideas from incogbyte/android-reverse-engineering-claude-skill
are incorporated here without adding it as a second runtime dependency: AAB/DEX
coverage, bundletool/apktool fallbacks, GraphQL/WebSocket discovery, and focused
security auditing.
Required workflow
- Confirm the artifact is owner-controlled, open source, provided for analysis, or otherwise expressly authorized for the requested reverse-engineering work.
- Fingerprint before full decompilation: packaging shape, native vs Flutter/RN/ Cordova/Xamarin, HTTP stack, obfuscation, notable SDKs, native libraries.
- Select the narrowest useful toolchain from evidence. For native Android, prefer jadx first; use Vineflower/Fernflower only when its output can resolve a real jadx limitation. Use bundletool for AAB and apktool only when resource decoding requires it.
- If a required tool is missing, install only that dependency from a trusted upstream. Prefer user-local/project-local installation, verify its version, and avoid broad package upgrades. Administrator/root elevation still requires explicit owner authorization.
- Inspect manifest and package structure before broad source reading. Separate first-party code from bundled libraries.
- For obfuscated Kotlin/KMP, use metadata/string/annotation evidence and R8 name
recovery before guessing ownership from mangled class names. Add
levyra-r8-proguardwhen shrinker behavior is part of the question. - Trace only the call flows needed for the requested outcome. Use entry point -> ViewModel/controller -> repository/service -> HTTP/client boundary when that structure exists.
- Extract APIs in two levels: a compact complete inventory first, then detailed analysis only for requested/high-value flows. Include GraphQL/WebSocket/Ktor when detected; do not assume Retrofit.
- Add
levyra-security-reviewfor exported components, transport/pinning, manifest permissions, hardcoded sensitive material, crypto, update integrity, or other trust-boundary findings. - Keep generated decompile output and reports outside tracked Levyra source unless the owner explicitly asks to commit a specific artifact/document.
Dynamic analysis boundary
Static analysis is the default. Frida or equivalent instrumentation is a separate explicit phase, not an automatic escalation.
Use dynamic instrumentation only on owner-controlled or explicitly authorized targets and only to answer the requested diagnostic question. It may be used for runtime observation, crash/root-cause diagnosis, call tracing, or verification of the owner's own software. Do not capture credentials, session secrets, private user data, or automate bypasses whose purpose is to gain access to protected third-party functionality.
Evidence and delivery
Record artifact hash/version when available, exact tools/versions used, the chosen decompiler path, warnings/partial-decompile limitations, and which findings are direct evidence versus inference. A decompiler's reconstructed Java is evidence about bytecode behavior, not proof of the original source text.
Apply docs/ai/ALWAYS_ON_AGENT_GUARDS.md and
docs/ai/EVIDENCE_GATED_COMPLETION.md throughout. Keep the production-file diff
at zero unless the active task explicitly requires a Levyra implementation
change based on the analysis.
Signals
- GitHub stars
- 164
- Forks
- 1
- Last commit
- Sep 2026
Advanced
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levyra-android-reverse-engineering- Source
- github.com/luc4n3x/levyra-deepsound