Analyze X-Kernel performance using workloads, baselines, and in-kernel diagnostics. Use when investigating latency regressions, soak benchmarks, throughput drops, scheduler hotspots (schbench/EEVDF), IO hotspots, lock_stat contention, or comparing…
Use when locating, triaging, or narrowing down X-Kernel problems, especially build failures, boot failures, kernel panics, syscall regressions, test failures, hangs, performance regressions, or unclear ownership across subsystems. This skill provides a…
Use when an AI agent needs a Linux source-grounded semantic baseline for X-Kernel memory-management design work, especially for mm struct, VMA, mmap, page faults, anonymous memory, file-backed mmap, COW, brk, madvise, msync, and mlock decisions.
Use when adding, running, or reviewing user-space regression tests for X-Kernel with the shared Starry Test Harness repository, especially for syscall semantics, CI/iter suite registration, guest-test case authoring, and result/log verification.