watchdog

SkillCloud & infra

Post-deploy monitoring. Use when verifying a deployed app is healthy after deploy or launch — auto-fires from launch/deploy. Checks HTTP status, response times, error detection, and smoke test report.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the watchdog skill

What this skill tells your AI

The instructions your AI receives, as published by rune-kit/rune in skills/watchdog/SKILL.md and read by ahel’s review.

Purpose

Post-deploy monitoring. Receives a deployed URL and list of expected endpoints, runs health checks, measures response times, detects errors, and returns a structured smoke test report.

Called By (inbound)

  • deploy (L2): post-deploy monitoring setup
  • launch (L1): monitoring as part of launch pipeline
  • incident (L2): current system state check during incident triage

Calls (outbound)

None — pure L3 utility.

Executable Instructions

Step 1: Receive Target

Accept input from calling skill:

  • base_url — deployed application URL (e.g. https://myapp.com)
  • endpoints — list of paths to check (e.g. ["/", "/health", "/api/status"])

If no endpoints provided, default to: ["/", "/health", "/ready"]

Step 2: Health Check

For each endpoint, run an HTTP status check using Bash:

curl -s -o /dev/null -w "%{http_code}" https://myapp.com/health
  • 2xx → HEALTHY
  • 3xx → REDIRECT (note final destination)
  • 4xx → CLIENT_ERROR (flag as alert)
  • 5xx → SERVER_ERROR (flag as critical alert)
  • Connection refused / timeout → UNREACHABLE (flag as critical)

Step 3: Response Time

For each endpoint, measure latency using Bash:

curl -s -o /dev/null -w "%{time_total}" https://myapp.com/health

Thresholds:

  • < 500ms → FAST
  • 500ms–2000ms → ACCEPTABLE
  • 2000ms → SLOW (flag as alert)

Step 4: Performance Signal Analysis

After collecting response times from Step 3, analyze for patterns that indicate root causes:

  • Consistently 2x+ slower than baseline (or > 2000ms with no apparent load): flag with PERF_WARN — investigate N+1 query or missing DB index
  • Endpoint cluster degradation: if 3+ endpoints share a pattern (all auth endpoints slow, all /api/* slow): flag PERF_WARN — connection pool saturation likely
  • Spike after deploy: compare with previous watchdog run if available — if an endpoint that was FAST is now SLOW, flag PERF_REGRESSION — correlate with recent git diff

If no previous baseline exists, skip spike detection and note INFO: no baseline — first run.

Output performance signals into a perf_signals list (separate from alerts).

Step 5: Error Detection

Scan responses for problems:

  • 4xx/5xx HTTP codes → log endpoint + status code
  • Response time > 2s → log endpoint + measured time
  • Connection timeout (curl exits non-zero) → UNREACHABLE
  • Empty response body on non-204 endpoints → flag as WARNING

Collect all flagged issues into an alerts list.

Step 6: Report

Output the following report structure:

## Watchdog Report: [base_url]

### Smoke Test Results
- [endpoint] — [HTTP status] ([response_time]s) — [HEALTHY|REDIRECT|CLIENT_ERROR|SERVER_ERROR|UNREACHABLE]

### Alert Rules Applied
- Response time > 2s → alert
- Any 4xx on non-auth endpoint → alert
- Any 5xx → critical alert
- Unreachable → critical alert

### Alerts
- [CRITICAL|WARNING] [endpoint] — [reason]

### Performance Signals
- [PERF_WARN|PERF_REGRESSION|INFO] [endpoint] — [diagnosis]

### Summary
- Total endpoints checked: [n]
- Healthy: [n]
- Alerts: [n]
- Perf Signals: [n]
- Overall status: ALL_HEALTHY | DEGRADED | DOWN

If no alerts and no perf signals: output Overall status: ALL_HEALTHY.

Output Format

## Watchdog Report: [base_url]
### Smoke Test Results
- / — 200 (0.231s) — HEALTHY
- /health — 200 (0.089s) — HEALTHY
- /api/status — 500 (1.203s) — SERVER_ERROR

### Alerts
- CRITICAL /api/status — HTTP 500

### Summary
- Total: 3 | Healthy: 2 | Alerts: 1
- Overall status: DEGRADED

Constraints

  1. MUST report with specific metrics — not vague "performance seems slow"
  2. MUST include baseline comparison when available
  3. MUST NOT generate false alarms — precision over recall
  4. MUST separate perf signals from error alerts — they are different severity channels
  5. MUST NOT call perf skill — watchdog is a detector, not a diagnoser

Sharp Edges

Known failure modes for this skill. Check these before declaring done.

Failure ModeSeverityMitigation
curl timeout treated as slow (not unreachable)HIGHNon-zero curl exit code = UNREACHABLE, not a response time measurement
PERF_REGRESSION reported without baselineMEDIUMOnly flag regression if a previous run exists — otherwise INFO: first run
All endpoints flagged SLOW because test env is slowMEDIUMNote environment context — add ENV: non-production detected if URL contains dev/staging/localhost
Perf signal without actionable diagnosisLOWEvery PERF_WARN must include a hypothesis (N+1, pool saturation, etc.)

Done When

  • All specified endpoints checked (HTTP status + response time measured)
  • All 4xx/5xx → alerts list, all SLOW → alerts list
  • Performance patterns analyzed → perf_signals list (or INFO: first run)
  • Structured Watchdog Report emitted with Alerts + Performance Signals + Summary
  • Overall status is ALL_HEALTHY, DEGRADED, or DOWN (never ambiguous)

Cost Profile

~500-1500 tokens input, ~300-800 tokens output. Sonnet for configuration quality.

Signals

GitHub stars
86
Forks
26
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
watchdog-rune-kit
Source
github.com/rune-kit/rune