Claude-skill-registry inspect-metrics

Operational metrics dashboard with anomaly detection from metrics endpoint or state file.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/inspect-metrics" ~/.claude/skills/majiayu000-claude-skill-registry-inspect-metrics && rm -rf "$T"

manifest: skills/data/inspect-metrics/SKILL.md

Step 1: Try Metrics Endpoint

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.

Step 2: Fallback — Read State File

Read

data/state.json

and compute metrics manually:

PR status distribution: count entries by
```
status
```
Review verdicts: iterate all
```
reviews[]
```
arrays across all PRs, count by
```
verdict
```
Errors by phase: for all PRs with
```
lastError
```
, count by
```
lastError.phase
```
Skip reasons: for all PRs with
```
status: "skipped"
```
, count by
```
skipReason
```

Note that state-derived metrics only reflect current state, not historical totals (unlike the live metrics endpoint which counts events since startup).

Step 3: Present Dashboard

Display metrics in organized tables:

PR Status Distribution

Status	Count
pending_review	N
reviewing	N
...	...
Total	N

Review Verdicts (lifetime / from state)

Verdict	Count	%
APPROVE	N	X%
REQUEST_CHANGES	N	X%
COMMENT	N	X%
unknown	N	X%

Errors by Phase

Phase	Count
diff_fetch	N
clone_prepare	N
claude_review	N
comment_post	N

Skip Reasons

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").

Step 4: Anomaly Detection

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.

Step 5: Time-Based Metrics

From state file, compute:

Most recent review: find the latest
```
lastReviewedAt
```
across all PRs, show age
Oldest active PR: find the earliest
```
firstSeenAt
```
among non-terminal PRs
Last error: find the most recent
```
lastError.occurredAt
```
, show age

Step 6: Health Verdict

Based on anomaly detection, output a single-line verdict:

HEALTHY — no anomalies detected
DEGRADED — only WARNING-level anomalies
UNHEALTHY — any CRITICAL-level anomaly

Format:

Health: HEALTHY | DEGRADED (N warnings) | UNHEALTHY (N critical, M warnings)

Notes

If neither the metrics endpoint nor state file is available, report that and stop
Percentages should be rounded to 1 decimal place
Show "N/A" for metrics that can't be computed from the available data source
Keep the dashboard compact — this is meant for a quick operational check