Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
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Post-deploy monitoring: watch production after a deploy and alert on regressions
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Watch a live application after deployment. Alert on errors and regressions. Compare against a pre-deploy baseline.
Two modes:
--baseline: capture the current state BEFORE deployingParse the user's arguments and detect the deployment context.
# Detect current branch and recent deploy commit
git branch --show-current
git log --oneline -5
# Auto-detect platform from config files
[ -f fly.toml ] && echo "PLATFORM: fly"
[ -f render.yaml ] && echo "PLATFORM: render"
[ -f vercel.json ] && echo "PLATFORM: vercel"
[ -f netlify.toml ] && echo "PLATFORM: netlify"
[ -f Procfile ] && echo "PLATFORM: heroku"
[ -f railway.toml ] && echo "PLATFORM: railway"
# Check for health endpoint
curl -sf "${URL}/health" -w "\n%{http_code}" 2>/dev/null | tail -1
curl -sf "${URL}/api/health" -w "\n%{http_code}" 2>/dev/null | tail -1
Create the working directory:
mkdir -p .canary/baselines .canary/reports .canary/screenshots
--baseline mode)Run this BEFORE deploying to capture the current healthy state.
For each page to monitor, record:
# For each page URL
for PAGE_PATH in "/" "/dashboard" "/settings" "/api/health"; do
SLUG=$(echo "$PAGE_PATH" | tr '/' '_' | tr -d '?&=')
RESULT=$(curl -sf -o /dev/null -w "%{http_code}|%{time_total}" "${BASE_URL}${PAGE_PATH}" 2>/dev/null)
STATUS=$(echo "$RESULT" | cut -d'|' -f1)
TIME_MS=$(echo "$RESULT" | awk -F'|' '{printf "%.0f", $2 * 1000}')
echo " ${PAGE_PATH}: HTTP ${STATUS}, ${TIME_MS}ms"
done
Save baseline to .canary/baselines/baseline.json:
{
"url": "<base-url>",
"timestamp": "<ISO-8601>",
"branch": "<branch-name>",
"commit": "<git-SHA>",
"pages": {
"/": { "status": 200, "time_ms": 450 },
"/dashboard": { "status": 200, "time_ms": 680 },
"/api/health": { "status": 200, "time_ms": 45 }
}
}
Then STOP and tell the user: "Baseline captured. Deploy your changes, then run /canary <url> to monitor."
If no pages were specified, auto-discover pages to monitor.
From the application:
# Check sitemap if available
curl -sf "${URL}/sitemap.xml" 2>/dev/null | grep -oP '(?<=<loc>)[^<]+' | head -10
# Check robots.txt for known paths
curl -sf "${URL}/robots.txt" 2>/dev/null | grep -i "allow\|disallow" | head -10
# Common paths to always check
echo "Always check: / /login /dashboard /settings /api/health"
Default pages to monitor if nothing found: /, and the homepage only.
Monitor for the specified duration (default: 10 minutes). Run a check every 60 seconds.
Each check cycle:
TIMESTAMP=$(date -u +%Y-%m-%dT%H:%M:%SZ)
CHECK_NUM=$((CHECK_NUM + 1))
for PAGE_PATH in "${PAGES[@]}"; do
# Check HTTP status and response time
RESULT=$(curl -sf -o /dev/null -w "%{http_code}|%{time_total}" \
--max-time 10 "${BASE_URL}${PAGE_PATH}" 2>/dev/null || echo "0|0")
STATUS=$(echo "$RESULT" | cut -d'|' -f1)
TIME_MS=$(echo "$RESULT" | awk -F'|' '{printf "%.0f", $2 * 1000}')
# Compare against baseline
BASELINE_STATUS=$(jq -r ".pages[\"${PAGE_PATH}\"].status // 200" .canary/baselines/baseline.json 2>/dev/null)
BASELINE_TIME=$(jq -r ".pages[\"${PAGE_PATH}\"].time_ms // 1000" .canary/baselines/baseline.json 2>/dev/null)
echo " [Check #${CHECK_NUM}] ${PAGE_PATH}: HTTP ${STATUS} (${TIME_MS}ms)"
done
Alert levels:
| Level | Condition | Trigger |
|---|---|---|
| CRITICAL | Page load failure | HTTP status is not 2xx, curl timeout, DNS failure |
| HIGH | New errors | Error rate increased vs baseline (console errors, 5xx responses) |
| MEDIUM | Performance regression | Response time exceeds 2x baseline |
| LOW | New broken links | Previously-working routes now return 404 |
Key principles:
When a CRITICAL or HIGH alert fires (2 consecutive checks):
CANARY ALERT
=====================================
Time: [check #N at Xs elapsed]
Page: [URL]
Level: [CRITICAL / HIGH / MEDIUM / LOW]
Finding: [what changed, be specific]
Baseline: [baseline value]
Current: [current value]
=====================================
Options:
A) Investigate now: stop monitoring, focus on this issue
B) Continue monitoring: wait for next check to confirm
C) Rollback: revert the deploy
D) Dismiss: known issue, continue monitoring
After monitoring completes (or user stops), produce a summary.
CANARY REPORT: [url]
=========================================
Duration: [X minutes]
Checks: [N total per page]
Pages: [N pages monitored]
Commit: [deployed SHA]
Status: [HEALTHY / DEGRADED / BROKEN]
Per-Page Results:
-----------------------------------------
Page Status Avg Time Alerts
/ HEALTHY 450ms 0
/dashboard DEGRADED 1100ms 1 medium (was 450ms)
/settings HEALTHY 380ms 0
/api/health HEALTHY 45ms 0
Alerts Fired: [N] (X critical, Y high, Z medium, W low)
VERDICT: [DEPLOY HEALTHY / DEPLOY HAS ISSUES (see alerts above)]
=========================================
Save report to .canary/reports/<date>-canary.md.
If the deploy is healthy and the user wants to update the baseline:
cp .canary/reports/latest-snapshot.json .canary/baselines/baseline.json
echo "Baseline updated to commit $(git rev-parse --short HEAD)"
See Phase 5 above for the full CANARY REPORT template.
Inline alert format (during monitoring):
[08:42:15] Check #3: /dashboard: ALERT HIGH, response time 1250ms (baseline: 420ms)
[08:43:15] Check #4: /dashboard: ALERT HIGH, response time 1180ms (baseline: 420ms)
-> Consistent across 2 checks. Firing alert.
/canary https://app.example.com # Monitor homepage for 10 min
/canary https://app.example.com --baseline # Capture baseline before deploying
/canary https://app.example.com --duration 5m # Monitor for 5 minutes
/canary https://app.example.com --quick # Single-pass health check (no loop)
/canary https://app.example.com --pages /,/dashboard,/api/health
/canary <url> --baseline.canary/baselines/ in git so any team member can run canary against the same baseline/ship: pre-deploy checklist (run before deploying)/land-and-deploy: full merge-to-verify pipeline (runs canary automatically)/qa: interactive QA testing before shipping$ARGUMENTS
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Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Assess a codebase across seven areas, including exposed credentials, security, dependencies, structure, and tests. Receive category scores, findings tied to file locations, and a prioritized improvement plan with smaller tasks that can be completed quickly.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Measure code patterns such as casts to any or disabled lint rules, then run repeated, targeted edits. Keep changes that improve the chosen metric, revert unsuccessful changes, and track results for each improvement loop.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Generate several separate solutions, compare them against criteria fixed in advance, and verify the selected result through executable checks or an independent reviewer. Keep a proof log documenting candidates, evidence, failures, and remaining limits.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Restore context after /clear by summarizing recent work and project state
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Launch and navigate the ccboard TUI/Web dashboard for Claude Code. Use when monitoring token usage, tracking costs, browsing sessions, or checking MCP server status across projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.