agentleFS
npownpow/claude-skills/monitor/SKILL.md

monitor

Skill4 starsChanged 6 months agoApache-2.0View on GitHub

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.

30 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use debug and research.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AnthropicSkill

    debug

    Structured debugging session — reproduce, isolate, diagnose, and fix. Trigger with an error message or stack trace, "this works in staging but not prod", "something broke after the deploy", or when behavior diverges from expected and the cause isn't obvious.

    Also in 3 projects that use this

  • NVIDIASkill

    research

    Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 26 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If --recurring: schedule next run

    line 21
  2. Distinctive:

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

    line 90
  3. Very specific:

    If one-shot health check (not --recurring) → produce report directly in-session.

    line 115
  4. Distinctive:

    If healthy → launch via sagaflow below.

    line 117
  5. Very specific:

    If unhealthy → log SAGAFLOW_UNAVAILABLE, proceed with in-session fallback.

    line 118

“Common” is measured: kept by at least 6 in 10 of the 26 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

PresetSourcesMetrics
--service NAMEObservability platform, tracingLatency p50/p99, error rate, throughput, instance count
--pipeline NAMEPipeline orchestratorSuccess rate, SLA compliance, last failure
--ciCI/CD platformBuild success rate, flaky test %, avg build time
--deploy APPDeployment platformDeploy state, canary score, pending constraints
--ml FLOWML platformRun status, latest metrics, accuracy trend
--code REPOGit historyTODO/FIXME count, test coverage, PR merge rate
--deps REPOpip/npm audit, CVE DBsOutdated count, critical CVEs, last updated
--docsDocumentation platformPages not updated in 90d, broken links
--team NAMEGitHub, Slack, JiraPR velocity, open issues, Slack activity
--oncallPagerDuty, incident logOpen 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"
)

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