Arbitrary write to RCE playbook. Use when you have an arbitrary write primitive (from heap exploitation, format string, or OOB write) and need to convert it into code execution by targeting GOT, hooks, _IO_FILE vtable, exit_funcs, TLS_dtor_list, modprobe_path, .fini_array, or C++ vtables.
Binary protection bypass playbook. Use when identifying and bypassing ASLR, PIE, NX/DEP, stack canary, RELRO, FORTIFY_SOURCE, CET, and MTE protections in ELF binaries to enable exploitation.
Expression Language injection playbook. Use when Java EL, SpEL, OGNL, or MVEL expressions may evaluate attacker-controlled input in Spring, Struts2, Confluence, or similar frameworks.
macOS process injection playbook. Use when you need to inject code into running or launching macOS processes via dylib hijacking, DYLD environment variables, XPC exploitation, Mach port manipulation, or Electron/Chromium abuse.
XSLT injection testing: processor fingerprinting, XXE and document() SSRF, EXSLT write primitives, PHP/Java/.NET extension RCE surfaces. Use when user-controlled XSLT/stylesheet input or transform endpoints are in scope.
Custom VM and bytecode reverse engineering playbook. Use when CTF challenges or protected software implement custom virtual machines with proprietary bytecode, dispatcher loops, or maze-style challenges.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Mobile SSL pinning bypass playbook. Use when intercepting HTTPS traffic from mobile applications that implement certificate pinning, public key pinning, or SPKI hash pinning on Android and iOS, including React Native, Flutter, and Xamarin frameworks.
Upgrade Apache Spark applications between major versions (2.x→3.x, 3.x→4.x). Covers build files, deprecated APIs, configuration changes, SQL/DataFrame updates, and test validation.
Supply-chain testing via package-manager dependency confusion: when internal package names resolve to attacker-controlled public registries, leading to malicious install and script execution. Use for npm/pip/gem/Maven/Composer/Docker manifest review and authorized red-team supply-chain exercises.
This skill should be used when the user asks to "create an automation", "schedule a task", "set up a cron job", or mentions automations, scheduled tasks, or cron scheduling in OpenHands Cloud.
CHAIN multiple existing skills into custom multi-step workflows. Programmable skill combinations with automatic handoffs. Create composite skills from building blocks with conditional logic.
テスト駆動開発（TDD）方法論に従って新機能の実装やバグ修正を行います。新機能の実装、バグ修正、既存機能の拡張時に使用します。RED→GREEN→REFACTORサイクルをテストファーストアプローチで厳格に遵守します。
TanStack Router file-based routing patterns including route creation, navigation, loaders, type-safe routing, and lazy loading. Use when creating routes, implementing navigation, or working with TanStack Router.
Next.js 15+ App Router development patterns including Server Components, Client Components, data fetching, layouts, and server actions. Use when creating pages, routes, layouts, components, API route handlers, server actions, loading states, error boundaries, or working with Next.js navigation and metadata.
Core React 19 patterns including hooks, Suspense, lazy loading, component structure, TypeScript best practices, and performance optimization. Use when working with React components, hooks, lazy loading, Suspense boundaries, or React-specific TypeScript patterns.
Core Node.js backend patterns for TypeScript applications including async/await error handling, middleware concepts, configuration management, testing strategies, and layered architecture principles. Use when building Node.js backend services, APIs, or microservices.
Comprehensive Android device control via ADB (Android Debug Bridge). Use when user asks about: Android device management, app installation/uninstallation, APK operations, package management, file transfer (push/pull), screenshots, screen recording, input simulation (tap/swipe/text/keyevents), shell commands, logcat viewing, device info (battery/memory/storage), automation scripts, wireless ADB connection, scrcpy mirroring. Keywords: adb, android, phone, tablet, device, apk, install app, uninstall app, screenshot, screen record, tap, swipe, type text, keyevent, logcat, push file, pull file, shell, package, activity, intent, broadcast, dumpsys, getprop, settings, input, sendevent, monkey, am start, pm list, device info, battery status, wireless adb, connect device.
Write, debug, and optimize CUTLASS and CuTeDSL GPU kernels using local source code, examples, and header references. Use when the user mentions CUTLASS, CuTe, CuTeDSL, cute::Layout, cute::Tensor, TiledMMA, TiledCopy, CollectiveMainloop, CollectiveEpilogue, GEMM kernel, grouped GEMM, sparse GEMM, flash attention CUTLASS, blackwell GEMM, hopper GEMM, FP8 GEMM, FP4 GEMM, blockwise scaling, MoE GEMM, StreamK, warp specialization CUTLASS, TMA CUTLASS, epilogue fusion, EVT (Epilogue Visitor Tree), pycute, Layout algebra, Swizzle pattern, GemmUniversal, KernelSchedule, EpilogueSchedule, CUTLASS collective builder, CUTLASS pipeline, or asks about writing high-performance CUDA kernels with CUTLASS/CuTe templates. Also use when the user wants to understand CUTLASS source code structure, compile CUTLASS examples, or debug CUTLASS template errors.
Write, debug, and optimize Triton and Gluon GPU kernels using local source code, tutorials, and kernel references. Use when the user mentions Triton, Gluon, tl.load, tl.store, tl.dot, tl.dot_scaled, triton.jit, gluon.jit, wgmma, tcgen05, TMA, tensor descriptor, persistent kernel, warp specialization, fused attention, matmul kernel, kernel fusion, tl.program_id, triton autotune, MXFP, FP8, FP4, NVFP4, block-scaled matmul, SwiGLU, top-k, triton_kernels, roofline analysis, Triton IR, TritonGPU dialect, MLIR Triton, PDL (programmatic dependent launch), cluster launch control, or asks about writing GPU kernels in Python. Also use when the user wants to understand Triton compiler internals, debug Triton kernel correctness, profile Triton kernel performance, or convert CUDA kernels to Triton.
