# Monitor

> |

- **Type:** Skill
- **Install:** `agentstack add skill-npow-claude-skills-monitor`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [npow](https://agentstack.voostack.com/s/npow)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [npow](https://github.com/npow)
- **Source:** https://github.com/npow/claude-skills/tree/main/monitor

## Install

```sh
agentstack add skill-npow-claude-skills-monitor
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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='' --arg preset=auto --arg recurring=false --await"
)
```

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [npow](https://github.com/npow)
- **Source:** [npow/claude-skills](https://github.com/npow/claude-skills)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-npow-claude-skills-monitor
- Seller: https://agentstack.voostack.com/s/npow
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.