# Monitor

> Use when the user asks to monitor, health-check, watch, or check status of services, pipelines, code, teams, builds, deployments, or CI. Also triggers for "is X healthy", "check on Y", "watch Z". Runs one-shot or recurring, parameterized by data source.

- Skill: `npow/monitor` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds@latest add npow/monitor`
- Raw SKILL.md: https://api.skillmd.com/api/skills/npow/monitor/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: npow (https://skillmd.com/u/npow)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/npow/monitor

---


# Monitor

## Strategy

1. Select preset (determines data source and key metrics)
2. Gather health data from the source
3. Compare against baseline/thresholds
4. Rate: healthy / degraded / critical
5. Format report
6. Alert if critical
7. If `--recurring`: schedule next run

Exit: report delivered. For recurring: runs until cancelled.

## Report requirements (every report MUST include)

- **Specific metric values**: exact numbers, not just "high" or "degraded"
- **Trend direction**: is each metric improving, stable, or worsening vs baseline?
- **Actionable items**: concrete next steps ranked by urgency, not just observations
- **Anomaly callouts**: flag anything outside expected range with the specific threshold breached


> **Note:** Placeholders like `{user_question}` in Agent prompts are filled by you (Claude)
> from the current task context. They are not template variables — read the user input,
> gather the relevant context, and substitute before spawning the agent.

## Agents

### GATHER phase

```
Agent(subagent_type="Explore", model="haiku", prompt="""
Gather health data for: {target}
Preset: {preset}

Data sources to check:
{preset_data_sources}

Key metrics to collect:
{preset_metrics}

Output: raw metrics with timestamps.
""")
```

### ASSESS + REPORT phase

```
Agent(model="sonnet", prompt="""
Health data:
{gathered_metrics}

Baseline (last {baseline_days} days):
{baseline_data}

1. Compare current vs baseline
2. Flag anomalies (>2 stddev from baseline)
3. Rate overall: HEALTHY / DEGRADED / CRITICAL
4. Format as a concise health report
""")
```

## Presets

| Preset | Sources | Metrics |
|---|---|---|
| `--service NAME` | Observability platform, tracing | Latency p50/p99, error rate, throughput, instance count |
| `--pipeline NAME` | Pipeline orchestrator | Success rate, SLA compliance, last failure |
| `--ci` | CI/CD platform | Build success rate, flaky test %, avg build time |
| `--deploy APP` | Deployment platform | Deploy state, canary score, pending constraints |
| `--ml FLOW` | ML platform | Run status, latest metrics, accuracy trend |
| `--code REPO` | Git history | TODO/FIXME count, test coverage, PR merge rate |
| `--deps REPO` | pip/npm audit, CVE DBs | Outdated count, critical CVEs, last updated |
| `--docs` | Documentation platform | Pages not updated in 90d, broken links |
| `--team NAME` | GitHub, Slack, Jira | PR velocity, open issues, Slack activity |
| `--oncall` | PagerDuty, incident log | Open incidents, MTTR, handoff notes |

## Cross-provider review

When cross-provider tools are available, run verification on a non-Claude model
in parallel for maximum blind-spot diversity.

## Flags

- `--recurring=INTERVAL` — repeat on schedule (daily, hourly, etc.)
- `--alert=CHANNEL` — notification channel for critical alerts
- `--baseline=N` — days of baseline data (default: 14)

## Examples

```
/monitor --service my-api
/monitor --pipeline etl-daily --recurring=daily
/monitor --ci --alert=#builds
/monitor --team platform-eng
/monitor --code --baseline=30
/monitor --oncall
```

## Execution routing (sagaflow-first)

**Sagaflow is the default execution path.** The in-session workflow above is the FALLBACK, used only when the sagaflow worker is confirmed unavailable.

**Routing sequence (mandatory before any in-session work):**
0. If one-shot health check (not `--recurring`) → produce report directly in-session. Do NOT route to sagaflow.
1. Run `sagaflow doctor`
2. If healthy → launch via sagaflow below. Stop. Do not run in-session.
3. If unhealthy → log `SAGAFLOW_UNAVAILABLE`, proceed with in-session fallback.

**Launch command:**
```
Bash(
  run_in_background=true,
  command="sagaflow launch monitor --arg target='<TARGET>' --arg preset=auto --arg recurring=false --await"
)
```