Maintaining macos health
Skill CodeAlive-AI/ai-driven-development/skills/maintaining-macos-health
Practices, protocols, and skills for AI-driven software development. Skills and safety hooks for Claude Code, Codex, OpenCode, Cursor, Antigravity, and any agent supporting the Agent Skills standard.
npx -y skills add CodeAlive-AI/ai-driven-development --skill maintaining-macos-healthAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Hands-on playbook for macOS disk cleanup, dev-machine optimization, and proactive health alerting. Use when the Mac is full or slow, when a process persistently burns CPU, when a kernel panic / watchdog timeout / vm-compressor-space-shortage / Jetsam event happened, when the user asks to free disk space, audit storage, set up disk/memory/CPU alerts, or restore the same monitoring on a new Mac. Built around Mole (`mo` CLI) for safety guards plus a custom LaunchAgent-based alerter for active warnings. Covers Apple Silicon laptops with heavy AI/Docker workloads. Not for general macOS support, hardware diagnostics, networking issues, GUI / window-manager bugs, Time Machine recovery, or broken app installs.
SKILL.md
16.5 KB, as published. Nobody here has run it
Maintaining macOS Health
Recovery and prevention playbook for macOS disk and memory crises. Validated against a real watchdog-timeout kernel panic on Apple Silicon caused by vm_compressor segments saturated to 100 % with the disk over 90 % full. The same playbook works for routine cleanup or first-time setup on a new machine.
Table of contents
- When to use
- Skill layout
- Core mental model
- Standard workflows
- Safety rules (non-negotiable)
- Domain quirks captured
- Outcomes scale
When to use
Trigger on any of:
- Disk free < 20 % or user complains about being out of space
- Watchdog-timeout / kernel panic / "no checkins from watchdogd"
- New
JetsamEvent-*.ipswithvm-compressor-space-shortage - "Mac is slow", swap > 6 GB, sustained Critical memory pressure
- A process persistently consumes a core, or the whole machine stays CPU-saturated
- User wants to set up monitoring/alerting from scratch
- Migration to a new Mac → restore the same alerter
- General "clean my Mac" / "audit storage" / "free space" requests
Skill layout
| File | Use for |
|---|---|
references/triage.md | First 5 minutes — which signal fired, which tier of cleanup to start with |
references/cleanup-tiers.md | Tiered cleanup playbook (10 tiers, zero-risk → discuss-first), copy-paste-safe shell blocks |
references/never-touch.md | Categories that must not be deleted even under sudo (Mole-derived blacklist + incident-derived additions) |
references/mole-techniques.md | What Mole does that we borrow: marker→target map for mo purge, safe-path validators, age thresholds |
references/alerting.md | Full alerter design: disk/memory/Jetsam critical triggers plus sustained CPU anomaly detection, incident lifecycle, hysteresis, notifier choices, install/restore commands |
assets/mac-health-check | Production-ready bash script (~250 lines, bash 3.2 compatible) |
assets/mac-health-action | Background action dispatcher for read-only Codex/Claude investigations and explicitly confirmed graceful process stopping |
assets/com.local.mac-health-check.plist | LaunchAgent plist with StartCalendarInterval (StartInterval is broken on laptops) |
assets/config.sh | Default config with safe thresholds |
assets/render-cleanup-plan.py | Interactive HTML cleanup-plan UI. Renders categorised checkboxes from a JSON of scan findings, serves on 127.0.0.1:18347, opens browser, waits for the user's selection, writes it to /tmp/cleanup-selection-<ts>.json. Used by Workflow A. |
assets/apply-cleanup-selection.py | The only sanctioned way to apply a cleanup selection. Reads selected_items from a selection JSON and executes each item's command field. Enforces protected-override check + path validation + Mole-compatible operations log. Prevents drift between what the user picked and what gets deleted. Supports --dry-run. |
Read the relevant reference before acting. Do NOT operate from memory of these files — the details are calibrated to a real incident and small changes break safety.
Core mental model
- Monitor passively — Stats menubar (
brew install --cask stats) — you see issues forming, not just when they explode. - Alert actively, diagnose quietly — disk, memory, Jetsam, and whole-system CPU saturation are critical. A single process burning CPU is a silent advisory only after a long sustained window; routine samples stay in the log.
- Cleanup tiers — start zero-risk (caches, orphan data), only escalate to project artifacts and sudo categories if needed. Mole's
mo purgeandmo cleanare the right primary tools. - Mole is the safety floor — even when running shell commands by hand, follow Mole's path-validation rules: never delete inside
/System,/bin,/usr,/etc,/var/dboutside specific allowlisted subpaths; bin/ only under .NET; vendor/ only under PHP; protect AI/password/VPN/keychain bundle IDs.
Standard workflows
A. "Free space NOW" (incident response)
- Triage — read
references/triage.md, identify which signal fired and how urgent. - Snapshot baseline —
df -h /System/Volumes/Dataand write down free GB. - Run all scans, don't delete yet —
duaudit of$HOMEsubdirs,mo clean --dry-run,mo purge --dry-run --debug,docker system df -v,~/Downloadsaudit. Capture everything; deletion comes only after user picks via the UI. - Resolve unknown items before building JSON — for every candidate > 500 MB whose purpose you cannot explain in one sentence (unfamiliar app, unfamiliar bundle ID, unfamiliar dotfolder, vendor-specific cache, ML model weights, VM image, etc.), research it first: check
references/never-touch.mdfor a known entry, then delegate a quick lookup to theweb-searchersubagent ("what is<path or bundle id>on macOS, is it safe to delete in 2026"). Wait for the answer, then write a concretedescription(1-3 sentences in the user's language) into the item — what it is, who created it, what feature uses it, what breaks if deleted, whether it auto-recreates. Never show the report with vague placeholders like "unknown" or "ML data" — that defeats the point of the UI. If a web lookup contradictsnever-touch.md, prefer the web answer (it's fresher) and propose an update to the reference file. - Build the data JSON — every candidate becomes a structured
item(id, label, path, size_bytes, age_days, kind, command, mandatorydescription, optionalprotected+warning). Write to/tmp/cleanup-data-<ts>.json. Use schema fromassets/render-cleanup-plan.pydocstring. - Render and open the cleanup UI:
The script starts a one-shot HTTP server onpython3 .../assets/render-cleanup-plan.py /tmp/cleanup-data-<ts>.json127.0.0.1:18347, opens the page in the user's default browser, and blocks until the user clicks Submit or Cancel. On submit it writes/tmp/cleanup-selection-<ts>.jsonand prints that path to stdout. Tell the user out loud: "браузер открыт — поставь галочки, нажми Submit, потом пингани меня". Then stop and wait. - After the user pings — read the selection JSON, render the user's choices back in chat (categories, item list, total GB, any protected overrides flagged ⚠), and ask one explicit confirmation before deleting. Don't run anything until they say "go".
- Apply via the helper script — never hand-rolled
rm:
The script readspython3 .../assets/apply-cleanup-selection.py /tmp/cleanup-selection-<ts>.jsonselected_itemsfrom the selection JSON and executes each item'scommandfield, with built-in safeguards: protected items must appear inprotected_overridesor are skipped; commands are validated against a hard-protected path list and a..-component check before execution; every action is logged to~/.config/mole/operations.login Mole-compatible TSV.--dry-runpreviews without executing. Do not write your ownrmblocks in the apply phase — that's how you delete items the user explicitly unchecked. The selection JSON is the single source of truth; if it's not inselected_items, it does not get deleted. Rundf -h /System/Volumes/Databefore and after for the user-visible delta. - Stop at goal — most users target 100 GB free. Don't go below that just for sport.
The Python script is bash-3.2-friendly, uses only stdlib, and is safe to run from inside the agent's shell. Hard-protected items (per references/never-touch.md) must always appear in the UI with "protected": true + a concrete warning string — the UI dims them and requires a per-item confirm dialog before they can be checked. Never omit a protected item that user data depends on (Telegram tdata, Bear database, password-manager containers, etc.) — visibility teaches the user the surrounding risk.
B. "Set up alerting" (new machine or first time)
- Copy
assets/mac-health-checkandassets/mac-health-actionto~/bin/(mkdir first; chmod +x). - Copy
assets/com.local.mac-health-check.plistto~/Library/LaunchAgents/. - Copy
assets/config.shto~/.config/mac-health/config.sh(mkdir first). brew install vjeantet/tap/alerter(NOT terminal-notifier — it's broken in 2026 on Sequoia/Tahoe).brew install --cask statsfor passive layer.launchctl load -w ~/Library/LaunchAgents/com.local.mac-health-check.plist.- First run permission prompt: open
alerteronce interactively (alerter --message test) so macOS asks for Notification Center permission. - Tell the user: 7-day calibration is silent (logs only). Edit
config.shafter a week if pattern noisy.
The calibration window applies to the original disk/memory/Jetsam critical sensors. CPU uses conservative developer-workstation defaults and starts immediately; process advisories are silent and deduplicated for the full incident lifetime.
Verify with launchctl list | grep mac-health (should show PID and exit 0) and tail -f ~/Library/Logs/mac-health/health.log.
C. "Already have alerter, but it stopped working / making noise"
Read references/alerting.md § Troubleshooting. Common causes:
- Stuck/old
terminal-notifier(the cask) instead ofalerter— replace. - LaunchAgent not loading after macOS update —
launchctl bootstrap gui/$(id -u) <plist>. - Notifications going to Script Editor — TCC permission was revoked, re-grant.
- Constant alerts during heavy dev work —
touch ~/.config/mac-health/silentto suppress.
D. "Uninstall an app cleanly"
mo uninstall <app> — Mole scans 12+ locations for app traces (Application Support, Containers, Group Containers, Caches, Preferences, Saved State, LaunchAgents, LaunchDaemons, login items, etc.). Always show dry-run first, never bypass.
Safety rules (non-negotiable)
- Never delete without dry-run + user confirmation for any tier ≥ 5 or any sudo operation.
- Never bypass
references/never-touch.md— even if user explicitly asks. Push back, explain the consequence. mo purgeandmo cleanalways with--dry-runfirst. Show estimated reclaim, get confirm.- For Time Machine backups:
tmutil delete <path>, neverrm. TM-tagged paths require thetmutilAPI. - For sudo cleanup of
/Library,/private/var/db/*: only the allowlisted subpaths fromreferences/never-touch.md§ Sudo allowlist. - No auto-cleanup hooks tied to alerts. Alerts notify; user decides. Documented anti-pattern (Google SRE, also confirmed by community 2025-2026 — see
references/alerting.md). - No auto-kill hooks tied to CPU alerts. A CPU advisory may offer
Stop Process…, but only as an explicit user action. Revalidate PID/executable identity and ownership, confirm, send SIGTERM first, and require a separate confirmation before SIGKILL. - Don't delete swap files.
rm /private/var/vm/swapfile*while running = guaranteed kernel panic. - Apply phase reads only the selection JSON. Never hand-roll
rmblocks or hard-code paths from the earlier scan when applying. Real incident: agent applied the default-selected recordings list from the original scan, ignoring that the user had unchecked them in the UI before submitting. The fix is structural — useassets/apply-cleanup-selection.pywhich iteratesselected_itemsfrom the selection JSON only.
Domain quirks captured
- macOS Tahoe (26.x) ships
/bin/bash3.2.57.set -u+local var(no init) = unbound on first reference. The shipped script handles this. - LaunchAgent does not inherit user PATH. Plist must declare
EnvironmentVariables.PATHand use absolute paths for interpreters. StartIntervalclock pauses during sleep on Apple Silicon laptops (radar 6630231). UseStartCalendarIntervalwith explicit minute entries (the shipped plist has all 12).terminal-notifieris effectively unmaintained (last release 2019-11) and silently fails on Sequoia/Tahoe Apple Silicon. Usealerterinstead.osascript display notificationfrom launchd attributes to "Script Editor" and is unreliable. Usealerterfrom launchd context.log show --last 6mis too slow (30+ s) for periodic checks. Poll/Library/Logs/DiagnosticReports/JetsamEvent-*.ipsinstead — async write delay is acceptable on a 5-min cadence.JetsamEvent-*.ipsfiles live in/Library/Logs/DiagnosticReports/(system-wide), NOT~/Library/Logs/DiagnosticReports/.- macOS
ps %cpuis a decaying average over up to one minute and is measured relative to one logical core, so a process may exceed 100 %. Whole-system CPU from the secondiostatsample is 0–100 % across the machine.iostatis much lighter than startingtopevery five minutes. - CPU notifications resolve an owning app without reading command arguments: first from known tool paths (Playwriter, SourceCraft, Logi Options+), then from the outer
.appbundle in the executable/parent chain, then from the executable fallback. Alerts show bothAppandProcessso helpers such asCodex (Renderer)are attributed to ChatGPT. - CPU counters reset after a gap longer than 15 minutes, so sleep and missed calendar firings cannot masquerade as consecutive high-CPU readings. Open incidents remain open but need fresh recovery readings before rearming.
- APFS purgeable space lags behind actual deletion by minutes. After cleanup,
dfmay not show the change immediately; wait or rundiskutil info /System/Volumes/Data | grep "Container Free". - Claude Desktop
vm_bundles/claudevm.bundle/is Claude Cowork, not "Claude Code sandbox" — it's a ~10 GB Ubuntu VM image (rootfs.img,sessiondata.img,efivars.fd,vmIP) for Anthropic's sandboxed code-execution feature. It is auto-provisioned at every Claude Desktop launch via an SHA1 integrity check, so its recent mtime ≠ user activity. Technically safe to delete (no chat/MCP impact), but Claude Desktop silently re-downloads ~10 GB on next launch and runs at ~55 % CPU while doing so. The Claude Code CLI does NOT use this bundle. Recommended classification: Tier 10 discuss-first with quit-Claude-Desktop pre-step and a warning that the bundle returns until Anthropic ships an opt-out toggle (open in anthropics/claude-code#57371). - General rule: if you encounter a folder/bundle you can't describe in one sentence (especially > 500 MB), don't guess — delegate a quick lookup to the
web-searchersubagent before writing the item'sdescription. See Workflow A step 4.
Outcomes scale
A representative recovery from a Mac that hit ~8 % free after long memory-pressure sessions on a heavily-loaded dev profile (Docker, multiple AI tools, IDEs, browsers):
- ~25 % of total disk capacity recovered in a 4-hour session
- Largest single contribution: project build artifacts via
mo purge(~30–50 GB across many scan paths) - Stale IDE installations + caches + preferences: ~10 GB
- Docker reclaim (unused images, dead builders, orphan volumes): ~10 GB
~/Downloadsreview (old installers, recordings, archived repos): ~15 GB- Package-manager caches (npm, pnpm, gradle, maven, cargo, brew): ~5 GB
- Sudo-tier cleanup (system logs, vendor-app depots): ~5–10 GB
Active alerter installed with 7-day calibration window; verified via synthetic disk-trigger test before going live. Stats menubar app installed for passive monitoring.
Numbers scale with workload and disk size. Light users will see less; heavy AI/Docker/IDE users will see more.