No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Tencent · Claude Skill · ★ 690
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is loli_profiler safe to install? View the security audit →
Overview LoliProfiler is a C/C++ memory profiling tool for Android games and applications. LoliProfiler supports profiling debuggable applications out of box. And offers engine specific (UnrealEngine4/Unity) modifications to enable profiling complex or production level games. Features Profiler client supports Windows 10/7 and Mac OSX Mojave and newer. Work with debuggable applications out of box. Support attaching to running application. Support multiple back-trace implementations. Support profiling complex games by doing some mods with your game engine. Support detecting c++ code memory leaks(Tested with Unreal Engine 4.26). Support profiling release build applications on rooted devices. Multiple data view modes: tree map/call tree/memory fragmentation. Builtin adb console to be able to exec command. CLI mode for automated profiling and CI/CD integration. AI (Claude Code) based memory growth report generation. MCP server for interactive heap sna
| Stars | 690 |
| Forks | 92 |
| Language | C++ |
| Category | Claude Skill |
| Quality Score | 58.1761970382353/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-12 |
| Created | 2021-03-04 |
| Platforms | claude-code |
| Est. Tokens | ~3243k |
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loli_profiler is Memory instrumentation tool with CI and AI support for android app&game developers.. It is categorized as a Claude Skill with 690 GitHub stars.
loli_profiler is primarily written in C++. It covers topics such as android, claude-code, cpp.
You can find installation instructions and usage details in the loli_profiler GitHub repository at github.com/Tencent/loli_profiler. The project has 690 stars and 92 forks, indicating an active community.
The top alternatives to loli_profiler on Agent Skills Hub include memsearch, claude-reflect, ai-devkit. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: