optimise

name

optimise

description

Read the latest benchmark results from the linux-system-optimisation benchmark folder, then propose and apply tuning — CPU governor + EPP, power-profiles-daemon profile, GPU power profile (NVIDIA / AMD / Intel vendor-specific), per-disk I/O scheduler, swappiness, vm.* sysctls, transparent hugepages, zswap/zram. Shows a before/after diff before applying. Persistent changes (/etc/sysctl.d, systemd units) require explicit confirmation; runtime-only changes apply directly. Triggers on "optimise my system", "tune based on benchmark", "apply optimisations".

Optimise

Read benchmark output → propose tuning → diff → apply.

Config

${CLAUDE_USER_DATA:-${XDG_DATA_HOME:-$HOME/.local/share}/claude-plugins}/linux-system-optimisation/config.json

benchmarks_dir points to the result store. Read the most recent results.json (highest ISO timestamp). If none exist → call benchmark first.

What to tune

Map findings → actions. Only propose actions backed by an actual benchmark observation; don't speculate.

Observation	Proposed action
CPU thermal throttling under load	Set governor to performance only when on AC; otherwise schedutil. EPP balance_performance. Check thermal paste / fan curve as a non-software follow-up.
Low CPU events/sec, governor was powersave	Switch governor (cpupower frequency-set -g performance or via power-profiles-daemon).
GPU hitting power cap on NVIDIA	nvidia-smi -pm 1 + raise power limit within hardware max via nvidia-smi -pl <W>.
AMD GPU stuck at low pstate	Set /sys/class/drm/card*/device/power_dpm_force_performance_level to auto or high.
Disk IOPS far below class baseline (NVMe < 50k randread)	Switch I/O scheduler: NVMe → none; SATA SSD → mq-deadline; HDD → bfq. Apply via udev rule.
Memory pressure / heavy swap	Lower vm.swappiness (default 60 → 10 on workstations with ≥16 GB RAM). Enable zram if not already.
Many minor faults / slow allocations	Enable transparent hugepages madvise mode.
Lots of dirty page writeback stalls	Tune vm.dirty_ratio / vm.dirty_background_ratio.

Apply protocol

1. Compute the diff. For each proposed change, capture current value (e.g. cat /sys/devices/system/cpu/cpu0/cpufreq/scaling_governor) and target value. Present as a unified table.
2. Classify each change as runtime (lost on reboot) or persistent (survives reboot — udev rule, sysctl.d file, systemd unit).
3. Apply runtime changes directly — the autonomy directive covers reversible local actions. Note each one as it happens.
4. For persistent changes, write to a single dedicated file per category so they're easy to revert:
   • /etc/sysctl.d/99-linux-system-optimisation.conf
   • /etc/udev/rules.d/60-linux-system-optimisation-ioscheduler.rules
   • /etc/systemd/system/linux-system-optimisation-gpu.service (only if GPU tuning needs persistence) Confirm once before writing the batch — not per file.
5. Reload the relevant subsystem: sysctl --system, udevadm control --reload && udevadm trigger, systemctl daemon-reload && systemctl enable --now <unit>.
6. Re-run benchmark and write a delta summary into the new result folder noting which tunings preceded it.

Safety

• Never raise GPU power limit above the hardware max reported by nvidia-smi -q | grep 'Max Power Limit'.
• Don't disable thermal protection. Don't write to /sys/class/thermal/*.
• Don't change CPU microcode or undervolt — out of scope.
• Always keep a backup of the original sysctl values inside the same benchmark result folder (pre-optimise-sysctl.conf).