Explorez les skills IA publiés de Ronin15 et consultez leurs instructions source.
Skills indexés
9Étoiles des dépôts des skills indexés
45Forks du dépôt
0Moyenne des étoiles par skill indexé
5Les étoiles d’un dépôt peuvent se répéter entre ses skills.
Generates complete test suite infrastructure (test scripts, functional tests, benchmark tests, output directories, CMake integration) for a new SDL3 HammerEngine system or manager following project conventions....
Generates comprehensive, professionally-formatted changelogs for SDL3 HammerEngine from git history. Analyzes code changes, runs tests, includes architect review, and produces detailed documentation following W...
Simplified memory profiling and leak detection for SDL3 HammerEngine using valgrind memcheck, AddressSanitizer, and massif. Identifies memory leaks, allocation hotspots, buffer reuse violations, and provides sy...
Review code changes for game/engine systems with a focused Game Systems Engineer mindset. Use when the user asks to review code, check consistency, or validate changes against AGENTS.md standards, especially fo...
Runs comprehensive code quality checks for SDL3 HammerEngine including compilation warnings, static analysis (cppcheck, clang-tidy), coding standards validation, threading safety verification, and architecture...
Generates professional performance analysis reports from SDL3 HammerEngine benchmark results including statistical analysis, comparison tables, visualizations, and recommendations. Use when preparing performanc...
Runs complete build validation pipeline for SDL3 HammerEngine including Debug build, smoke test execution, core test suite, and summary report generation. Use when the user wants to quickly validate their chang...
Verify dependency structure and architecture health for SDL3 HammerEngine. Detects circular dependencies, excessive coupling, layer violations, header bloat, and provides dependency graph visualization. Ensures...
Runs performance benchmarks for SDL3 HammerEngine and detects regressions by comparing metrics against baseline. Use when testing performance-sensitive changes to AI, collision, pathfinding, particle systems, o...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.