macOS Watchdog

Select event or periodic triggers for the problem being observed, then apply the quiet-watchdog contract before remediation.

Bind a watchdog's lifecycle to its premise state. When it cannot repair the condition (broken WiFi, user quit the target app, prerequisite state gone), stand down without waiting for a human to disable it.

Entry decision tree

The situation is…	Go to
Installing a NEW watchdog from scratch	Select the trigger through references/event-driven-observers.md, then § Deploy and § The quiet-watchdog contract
Installing, upgrading, reusing or starting a persistent Python job	§ Persistent Python runtime
An existing watchdog misbehaves (spam, re-launches apps, hammers)	§ The quiet-watchdog contract, diagnose which clause it violates
Stopping / disabling / restarting a job	§ Stop semantics
Retiring a job and its tool permanently	§ Stop semantics → Decommissioning a job permanently
plist key details (KeepAlive forms, domains, logging, resource limits)	references/launchd-plist-reference.md
Choosing between event-driven and periodic for a source of truth	references/event-driven-observers.md § Select event vs periodic
Deploying / accepting an event-driven observer (WatchPaths, FSEvents, inotify-style)	references/event-driven-observers.md § Deployment SOP and § Acceptance SOP
Checking whether a plist edit is active, or comparing job argv / explicit ENV / configured paths / scheduling keys	Run scripts/inspect_native_job.py with the exact expected plist; read references/native-job-readback.md for result, scheduling-flag and source-selection rules
Setting up or recovering an already-authorized persistent calendar job with delivery deadlines	references/launchd-plist-reference.md § Calendar deadlines and recovery; check overdue work and actual delivery separately
Cooldown/backoff/notification-throttle patterns + sanitized war stories	references/quiet-watchdog-patterns.md
SRE alert layering (page vs ticket, fatigue numbers)	references/alert-discipline.md
A watchdog alert appears under Script Editor or its sender is unclear	references/alert-discipline.md § Message content; inspect the delivered card

The quiet-watchdog contract

Before shipping or blessing any watchdog, every clause below must hold. Each clause exists because a real watchdog violated it.

1. Premise-state self-check — it knows when it has no job

The script's first act on every run: verify the state that justifies its existence still holds. If not, exit silently — no remediation, no notification, no side effects.

• A proxy-repair watchdog checks the proxy app is running first; user quit it → skip the cycle.
• A "did the config switch back" watcher checks the config state it watches; already switched → self-stop, not another round of misleading notifications. (Real case: a recovery watcher kept firing for 2h after its premise resolved, sending 3 spurious notices, because nothing told it to stop.)

2. Remediate first, page only on sustained failure

Detection stays honest on every cycle, but the disruptive action defers until the failure persists across N consecutive cycles (patient mode). Rationale: oscillating chains self-recover in minutes; a force-reconnect on a self-limiting blip is net-harmful. Measure your system's real self-recovery window before choosing N (one chain's 94-min observatory run showed ≤3 min self-recovery → N=2 cycles at 5-min interval).

When the trigger aggregates several independent sources into one verdict (not a single health check), the cross-source agreement fraction is a second, separate parameter from N — don't default to "all sources must agree." An all-or-nothing gate produces a false negative on exactly the correlated-but-partial incident the watchdog exists to catch, because real failures rarely take every source down at once (real case: a 9-source collection-health gate required 9/9 failing and missed a live incident sitting at 6/9; recalibrating against the actual incident data to a ≥60%-of-sources threshold caught it while three-fixture testing at 0%/11%/100% confirmed it still tolerated a single-source blip). Calibrate breadth (what fraction must agree) against real historical failure data the same way you calibrate depth (N) — a threshold picked from what "sounds strict enough" is a guess, not a calibration.

Escalation ladder (cheap → disruptive): refresh state → restart connection → remote repair. Each rung verifies before climbing.

3. Escalating auto-cooldown — an unfixable environment means silence

When the full repair ladder fails, the environment is unfixable by the watchdog (broken WiFi, captive portal, dead upstream). The naive behavior — re-run the entire ladder + notification every interval forever — is exactly "the watchdog keeps re-launching the app every 10 minutes."

ThrottleInterval does not fix this: it throttles process respawn, is a fixed delay with no backoff, and does nothing for a job that exits 0 after spamming. Cool-down must live in the application layer:

• Record consecutive exhausted rounds in a state file.
• After each exhausted round, stand down for an escalating tier (e.g. 30 min → 2 h → 6 h, last tier repeats).
• One notification when entering cool-down; zero during it. On tier expiry, retry one round; any real heal clears the counter and the cool-down state.
• A manual pause [duration] command with a TTL state file is the fallback — but the auto path must work with no human command at all. A disable mechanism that requires the user to remember a command is not a mechanism.

Reusable implementation: scripts/watchdog-cooldown.sh (source it; provides paused_any, record_exhausted, clear_exhausted, cmd_pause/cmd_resume).

4. Never resurrect what the user explicitly quit

On macOS, open <url-scheme> launches the app when it isn't running, and open without -g steals foreground. A watchdog whose remediation uses URL schemes (or open -a, or restarting a GUI app) will read to the user as "I quit it and it came back."

Gate every such action: check the target process is alive before invoking its scheme, and pass -g so a legitimate action never pops a window. If the user quit the app mid-remediation, abort the ladder — cleanup traps must honor the same gate, or the "ensure connected on exit" fallback becomes the resurrector.

Deploy (mechanics that bite)

Before deploying or integrating an existing periodic observer, apply references/probe-cost.md. Require bounded observation work and a completed native launchd round; importing an existing script does not certify its cost or verdict.

Before declaring configuration active, use the native readback helper through references/native-job-readback.md. Read explicit ENV from the job's own block; do not take the first matching key from default or inherited environment sections. Verify the completed business round separately from registration or process state.

1. Location: user agent → ~/Library/LaunchAgents/ (GUI session context: can open apps, show notifications); system daemon → /Library/LaunchDaemons/ (root, no GUI access). Choose by whether the job needs the user's GUI session, not by habit.
2. plist: for periodic jobs start from assets/launchagent.template.plist; for event jobs follow references/event-driven-observers.md and its plist reference. Validate with plutil -lint. ProgramArguments element 0 = absolute path; never rely on shell PATH inheritance.
3. Load/reload: before replacing or stopping an existing job, apply the ownership, active-work and pending-intent checks in references/event-driven-observers.md § Deployment SOP. For an authorized idle job, load with launchctl bootstrap gui/$(id -u) <plist>; after a plist edit, bootout then bootstrap. Request one run of an idle owned job with launchctl kickstart gui/$(id -u)/<label>; -k terminates an existing instance and is not a routine test. kickstart -k on an instantly-exiting job is a throttle trap, not a latency probe: the kill+respawn collides with the 10 s ThrottleInterval, producing spawn failed, error=89 (ECANCELED) and respawns on 10.01–10.03 s beats, so the call blocks ~11–20 s. Measured 2026-10-20: 108/110 gaps at 10.01–10.03 s while plain kickstart returned sub-second. Do not read that blocking as launchd congestion.
4. Logs: StandardOutPath/StandardErrorPath are non-negotiable (without them failures vanish), plus in-script log rotation (cap ~1 MB).
5. Idempotency guard: re-running your deploy must not double-install. For periodic jobs only, use scripts/new-launchagent.sh <label> <script> <interval> after the replacement checks above; it can boot out a loaded job. For event jobs use the event SOP. In both cases, verify loaded configuration through the native helper and completed work separately.
6. TCC / Full Disk Access: a LaunchAgent reading protected files needs a working grant for its effective permission subject. Use macos-permissions to inspect TCC attribution and verify a protected read from the actual job; the shell's interpreter path alone does not decide this.
7. Batch throttling by default: any watchdog loop that spawns work (replays, fuzz, batch scans, parallel API calls) needs an explicit rate cap as a default parameter, not a later optimization. To the machine, an unthrottled loop and a runaway process are indistinguishable (real case: an unthrottled test replay forked 1,041 processes/sec for 7 minutes and pushed the die to 83 °C).
8. Browser side-effect acceptance: a successful data fetch alone does not prove a browser-backed watchdog is ready. The deploying operator must declare a budget for task-owned spaces and pages, then independently inventory them across multiple rounds, including injected initialization and cleanup failures. Counts must stay within that lifecycle budget; protect user-owned and unknown-origin pages throughout. If the task requires no focus stealing, independently observe the foreground app and visible windows during those rounds; CDP success is not focus evidence. For ego lite lifecycle, locking, ownership conflicts and cleanup readback, load the named Skill ego-lite-use when installed. Otherwise use the owning browser tool's documented lifecycle while meeting the same budget and readback requirements. Missing resource observations, or missing focus observations when no focus stealing is required, leave acceptance incomplete.
9. Sub-minute StartInterval is a BTM transition tax — prefer a KeepAlive loop for high-frequency probes. Every periodic firing costs two launchd job state transitions (running + exited), and backgroundtaskmanagementd converts each into a store write plus a 250 ms-coalesced distributed userDataDidChange broadcast that drives LoginItems.appex full monitor rebuilds — the amplifier behind the 2026-10-06/10-17 watchdog panics. Three 30 s jobs alone cost ~16,200 transitions/day. A persistent job running an in-process loop (period = max(interval, runtime+1s)) keeps the cadence with zero steady-state transitions. Measured effect of converting the three biggest offenders: BTM-triggering monitor updates 0.45/s → ~0.20/s.
10. macOS zeroes XPC_SERVICE_NAME for spawned children — identity guards break when you wrap the probe. A launchd job process reads its own label, but every child it spawns (bash/sh/python) reads XPC_SERVICE_NAME=0, and export does not survive exec (measured on 27.0.1 with a dedicated probe job). A script whose guard is [ "$XPC_SERVICE_NAME" = <label> ] passes only when the script IS the job process. Wrap it in a loop/driver and the probe becomes a grandchild: the guard rejects 100% of iterations while launchctl shows state=running — one collector produced zero rows for 75 minutes. Pass identity through a different variable the driver sets (e.g. <PROJECT>_CALLER_LABEL via argv) and have the guard accept it as an alternative; direct execution stays refused because neither variable is set in a human shell.

Persistent Python runtime

For a persistent Python job, separate dependency preparation from normal startup:

• Install/upgrade: use the owning installer's explicit prepare action to create a persistent environment outside uv's cache from retained locked inputs. Bind the selected Python series, complete frozen distribution set and base interpreter to that installation. Keep dependency changes in this phase.
• Reuse: execute the environment's actual Python to compare its series and complete installed distribution names/versions with those frozen inputs, and verify its resolved base Python still exists and runs. A ready marker or a matching Python series alone does not validate the environment. Reject an empty, mismatched or broken environment; resume the authorized prepare action rather than silently accepting it.
• Run: register the absolute environment Python path in ProgramArguments and invoke the service entry directly. Fail visibly when that runtime is missing or invalid; do not silently fall back to uv run, another interpreter, or an install during startup. Check inherited variables and startup hooks when they could redirect the selected runtime. Finite maintenance scripts may still use their declared uv run workflow.

Before switching an existing job, retain the ownership, active-work and pending intent checks from § Deploy. Preserve its canonical configuration and rollback target; compare the live configuration with the inspected version immediately before replacing it, and stop on drift. Use the existing native readback and completed business-round acceptance through the actual consumer; a marker, PID or HTTP health response does not replace that result. The deploying operator owns these checks; this Skill does not supply a generic environment installer.

Keep permission attribution separate from Python environment selection. When a native executable needs an already authorized launcher's FDA identity, follow macos-permissions and its measured uv attribution case. If the real protected read proves that exact uv launcher is required, retain the verified responsibility chain. For a native executable, the installed uv's supported uv run --no-project --offline --no-cache -- <absolute-binary> ... form can avoid the shared main cache while preserving that launcher; verify the same protected operation from the real job before accepting it. Do not generalize this exception to Python dependency startup. --no-cache uses a temporary cache; it does not promise zero temporary disk use or, for other Python tasks, zero downloads.

Consult uv's environment-use guidance for direct environment execution and its cache documentation for --no-cache.

Stop semantics (the deprecated trap)

Before stopping or replacing a job, apply the ownership and active-work checks in § Deploy and the current task's authorization boundary.

Intent	Command
Stop now, allow re-bootstrap later	launchctl bootout gui/$(id -u)/<label> (daemon: sudo launchctl bootout system/<label>)
Prevent later loads across login (stop a loaded job separately)	launchctl disable user/$(id -u)/<label> (reverse: enable)
Edit then reload	bootout → edit plist → bootstrap

Use bootstrap/bootout instead of deprecated load/unload. When a job must remain disabled across later loads, apply disable; stopping an instance alone does not establish that persistent override.

A temporary job that stays loaded keeps paying the § Deploy-9 transition tax (its every firing still feeds BTM broadcasts). When the task it served is done, disable it — do not leave a dead-purpose periodic job running because stopping it felt irreversible: disable is fully reversible (enable + bootstrap), and the plist can stay on disk as the re-enable path.

Decommissioning a job permanently

Retiring a job's whole line (job + plist + tool) is a different operation from stopping one, and it is safe to be thorough: every step except the last is recoverable.

1. Stop and capture. bootout a loaded job; an already-disabled idle job has nothing running. Read the plist once (plutil -p) and keep its content in the session record — it names the tool path, log paths, and schedule you are about to remove.
2. Remove the plist from ~/Library/LaunchAgents/. A leftover launchctl disable override for the label is inert once the plist is gone; do not chase it.
3. Prove zero references before deleting the tool: grep the owning repo for the label and the tool name. Hits confined to the tool's own directory mean nothing imports, schedules, or documents it.
4. Delete the tool through the repo's normal PR flow — git history is the backup. After the merge lands, remove regenerable residue (__pycache__) from the checkout.
5. Keep the data/log directory by default (wherever the plist pointed, e.g. ~/.local/share/<tool>/): it is small, it holds the config a revival would need, and deleting it is the only irreversible step — offer it explicitly instead of cleaning silently.

Measured 2026-10-20 (wechat-print retirement): an every-minute StartCalendarInterval job had cost 2,880 launchd transitions/day of § Deploy-9 BTM tax while emitting nothing but failure logs for six days.

Troubleshooting quick map

Symptom	First check
"It re-launches the app I quit"	URL-scheme/open calls missing the process-alive gate (clause 4)
"It spams the same repair every few minutes"	No exhausted-round cool-down (clause 3); also check the ladder's failure path doesn't reset its dead-counter
"It reports healthy through a real outage"	Health check certifies only the path it probes — one green probe ≠ all planes healthy (add the second plane's probe)
"bootout didn't stick / it came back"	Confirm the exact domain/service target and who bootstrapped it again; for a persistent stop follow § Stop semantics
Silent no-runs	StandardErrorPath missing → failures invisible; then log show --predicate 'process == "launchd"' --last 15m
"log mtime is fresh" but the job is actually failing	out.log all-green is not health — a failed pass may write nothing (set -e + prints-verified-only-on-success), so the last-success timestamp stays fresh forever. Judge the failure path (err.log / last-exit status), not success-side freshness (Pattern 7)
After bootout+bootstrap, "the data file has a recent row" is not proof the new job works	The OLD job's final row can land inside your freshness window (real case 2026-10-20: a probe conversion passed a 75 s freshness check while the new job's every iteration was rejected by its identity guard for 75 min). Anchor verification to the NEW job: rows timestamped after the new PID's start, or per-iteration status rows; state=running never proves the collector writes
Works interactively, fails under launchd	TCC/FDA on the wrong interpreter; PATH assumptions in ProgramArguments
Observation becomes slower as history grows	Audit cold, warm and delta work using references/probe-cost.md; caching bytes does not bound parsing or queries

Details and the sanitized war stories behind each clause: references/quiet-watchdog-patterns.md.