a11y-ally
Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse,…
Use when querying test history, analyzing flakiness rates, tracking MTTR, or building quality trend dashboards from test execution data.
$ npx -y skills add proffesor-for-testing/agentic-qe --skill test-metrics-dashboard --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/test-metrics-dashboardContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when querying test history, analyzing flakiness rates, tracking MTTR, or building quality trend dashboards from test execution data.
name: test-metrics-dashboard description: "Use when querying test history, analyzing flakiness rates, tracking MTTR, or building quality trend dashboards from test execution data." user-invocable: true
Data & Analysis skill for querying test execution history, identifying trends, and surfacing actionable quality metrics.
/test-metrics-dashboard
| Metric | Formula | Target | Alert | |--------|---------|--------|-------| | **Pass Rate** | Passed / Total | > 95% | < 90% | | **Flakiness Rate** | Flaky / Total | < 5% | > 10% | | **MTTR** | Avg time from failure to fix | < 4 hours | > 24 hours | | **Execution Time** | Total suite duration | < 10 min | > 20 min | | **Coverage Delta** | Current - Previous | >= 0% | < -2% |
# Export Jest results to JSON
npx jest --json --outputFile=test-results/$(date +%Y-%m-%d).json
# Parse results for dashboard
jq '{
date: .startTime,
total: .numTotalTests,
passed: .numPassedTests,
failed: .numFailedTests,
duration_ms: (.testResults | map(.endTime - .startTime) | add),
pass_rate: ((.numPassedTests / .numTotalTests) * 100),
flaky: [.testResults[] | select(.numPendingTests > 0)] | length
}' test-results/$(date +%Y-%m-%d).json# Compare last 5 runs
for f in $(ls -t test-results/*.json | head -5); do
jq --arg file "$f" '{
file: $file,
pass_rate: ((.numPassedTests / .numTotalTests) * 100 | floor),
duration_s: ((.testResults | map(.endTime - .startTime) | add) / 1000 | floor)
}' "$f"
done# Find most frequently failing tests across runs for f in test-results/*.json; do jq -r '.testResults[] | select(.numFailingTests > 0) | .testFilePath' "$f" done | sort | uniq -c | sort -rn | head -10
Store dashboard data in `${CLAUDE_PLUGIN_DATA}/test-metrics.log`:
2026-03-18|95.2|4.1|312|82.5|3
Format: `date|pass_rate|flakiness_rate|duration_s|coverage_pct|failed_count`
Read history for trend detection:
# Coverage trending down?
tail -5 "${CLAUDE_PLUGIN_DATA}/test-metrics.log" | awk -F'|' '{print $5}' | sort -n | head -1Feeds into:
AI-powered quality engineering agents that generate tests, find coverage gaps, detect flaky tests, and learn your codebase patterns — across 11 coding agent platforms.
Repo: proffesor-for-testing/agentic-qe
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