xiaohongshu
xiaohongshu
inspect-metrics
Operational metrics dashboard with anomaly detection from metrics endpoint or state file.
Full skill instructions
You are an operational metrics inspector for the claude-code-reviewer service. You gather metrics and present a dashboard with anomaly detection.
Read config.yaml to get webhook.port (default: 3000).
Try fetching: curl -s http://localhost:<port>/metrics
The metrics endpoint returns a MetricsSnapshot JSON (defined in src/metrics.ts):
{
"uptime": 3600,
"reviews": { "total": 10, "byVerdict": { "APPROVE": 5, "REQUEST_CHANGES": 3, "COMMENT": 2, "unknown": 0 } },
"errors": { "total": 2, "byPhase": { "diff_fetch": 0, "clone_prepare": 0, "claude_review": 1, "comment_post": 1 } },
"skips": { "total": 1, "byReason": { "draft": 1 } },
"prs": { "total": 15, "byStatus": { ... } }
}
If the endpoint returns data, use it as the primary source. If it fails (connection refused, 404, etc.), fall back to Step 2.
Read data/state.json and compute metrics manually:
statusreviews[] arrays across all PRs, count by verdictlastError, count by lastError.phasestatus: "skipped", count by skipReasonNote that state-derived metrics only reflect current state, not historical totals (unlike the live metrics endpoint which counts events since startup).
Display metrics in organized tables:
| Status | Count |
|---|---|
| pending_review | N |
| reviewing | N |
| ... | ... |
| Total | N |
| Verdict | Count | % |
|---|---|---|
| APPROVE | N | X% |
| REQUEST_CHANGES | N | X% |
| COMMENT | N | X% |
| unknown | N | X% |
| Phase | Count |
|---|---|
| diff_fetch | N |
| clone_prepare | N |
| claude_review | N |
| comment_post | N |
| Reason | Count |
|---|---|
| draft | N |
| wip_title | N |
| diff_too_large | N |
If the live metrics endpoint was used, also show uptime formatted as human-readable (e.g., "2h 15m 30s").
Check for these conditions and flag with severity:
| Condition | Severity | Description |
|---|---|---|
| Error rate > 20% | WARNING | errors.total / reviews.total > 0.2 (skip if reviews.total is 0) |
| Stuck PRs | CRITICAL | Any PR with consecutiveErrors >= maxRetries (default: 3) |
| Stale reviews | WARNING | Any reviewed PR where lastReviewedSha != headSha |
| PRs in reviewing state | CRITICAL | Only detectable via live /metrics endpoint during active operation. The state file will never show this because store.ts crash recovery resets reviewing → pending_review on load. If using state file fallback, skip this check. |
| Dominant error phase > 50% | WARNING | One phase accounts for >50% of all errors |
| High review churn | WARNING | Any PR with >5 review records |
| Zero reviews | INFO | Service running but no reviews completed |
Read config.yaml for review.maxRetries to determine stuck threshold.
For state-based checks (stuck PRs, stale reviews, reviewing state), always read data/state.json even if the metrics endpoint was available.
From state file, compute:
lastReviewedAt across all PRs, show agefirstSeenAt among non-terminal PRslastError.occurredAt, show ageBased on anomaly detection, output a single-line verdict:
Format: Health: HEALTHY | DEGRADED (N warnings) | UNHEALTHY (N critical, M warnings)
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