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.
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.
Use this skill when optimizing token usage, reducing response verbosity, or working in high-volume development sessions. Trigger for any mention of token savings, cost optimization, concise output, compressed responses, or the --format=concise/ultra flags. Also applies during repetitive tasks, quick iterations, simple clear requests, or when the user activates token-efficient mode. This is a cross-cutting optimization that applies to all other skills.
Comprehensive error handling patterns for Python and TypeScript applications. Use this skill whenever writing try/catch blocks, creating custom error classes, implementing retry logic, designing error boundaries in React, building API error responses, or handling failures gracefully. Trigger for any code dealing with exceptions, error propagation, graceful degradation, or fault tolerance.
Environment-variable expression expansion syntax for Protobuf config fields annotated with enable_expression. Use when working with config templates, YAML deployment values, or expression syntax.
Improves Cairo performance after correctness is established. Trigger on "optimize", "gas usage", "reduce steps", "profile", "BoundedInt", "storage packing", "benchmark". Guides profiling, arithmetic optimization, and bounded-int hardening.
Adapt code to work with a GPU node's installed environment. Use when an experiment fails due to dependency version mismatches, import errors, missing packages, or API incompatibilities between the code's expected environment and what's actually installed on the GPU node. Triggered by errors like 'ModuleNotFoundError', 'ImportError', version conflicts, or when the user says 'adapt this code to the environment'.
Develop and maintain the SimpleLLMFunc framework itself. Use when changing framework internals, tests, docs, specs, runtime primitives, decorator behavior, tool plumbing, event streams, PyRepl integration, or contributor-facing project structure and conventions.
Use when optimizing VM Initializing-to-Running latency while preserving functionality and low implementation complexity.
Deep expertise in Yii 2 framework internals — modules, debug module architecture, component system, DI container, event system, request lifecycle, and extension points. Use when implementing or modifying the Yii 2 adapter, writing collectors, or debugging integration issues.
Deep expertise in Symfony internals — DI container compilation, bundles, compiler passes, event dispatcher, profiler/toolbar architecture, config tree builder, and how to integrate without breaking user config. Use when implementing or modifying the Symfony adapter.
Python library implementation skill for creating modules in lib/. Use when user says "create library", "implement module", "add to lib/", "python library", "helper functions", "utility module", "layer module", "python module", "shared utilities", "create helper".
Generate code mutations for Kubernetes operator controllers to enable mutation testing. Applies operator-specific mutations to reconciliation logic, error handling, and API interactions.
エラーハンドリングのベストプラクティスを適用するスキル。回復可能性を基準にしたエラー設計、 Either/Result型の使用、ドメインエラーとシステムエラーの適切な分類を支援する。コードレビュー、 新規実装、リファクタリング時にエラー処理パターンの改善が必要な場合に使用。対象言語: Go, Rust, Scala, Java, TypeScript, JavaScript, Python。トリガー：「エラー処理を改善して」 「Result型を使いたい」「例外設計をレビューして」「回復可能なエラーの設計」といった エラーハンドリング関連リクエストで起動。
