15582e2538
## New Skill: qa-expert (v1.0.0) Comprehensive QA testing infrastructure with autonomous LLM execution: - One-command QA project initialization with complete templates - Google Testing Standards (AAA pattern, 90% coverage targets) - Autonomous LLM-driven test execution via master prompts (100x speedup) - OWASP Top 10 security testing (90% coverage target) - Bug tracking with P0-P4 severity classification - Quality gates enforcement (100% execution, ≥80% pass rate, 0 P0 bugs) - Ground Truth Principle for preventing doc/CSV sync issues - Day 1 onboarding guide (5-hour timeline) - 30+ ready-to-use LLM prompts for QA tasks - Bundled scripts: init_qa_project.py, calculate_metrics.py ## Documentation Updates - Updated marketplace to v1.10.0 (16 → 17 skills) - Updated CHANGELOG.md with v1.10.0 entry - Updated README.md (EN) with qa-expert skill section - Updated README.zh-CN.md (ZH) with skills 11-16 and qa-expert - Updated CLAUDE.md with qa-expert in available skills list - Updated marketplace.json with qa-expert plugin entry ## SOP Improvements Enhanced "Adding a New Skill to Marketplace" workflow: - Added mandatory Step 7: Update README.zh-CN.md - Added 6 new Chinese documentation checklist items - Added Chinese documentation to Common Mistakes (#2, #3, #4, #5, #7, #8) - Updated File Update Summary Template (7 files including zh-CN) - Added verification commands for EN/ZH sync - Made Chinese documentation updates MANDATORY Total: 17 production-ready skills 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
95 lines
2.8 KiB
Python
95 lines
2.8 KiB
Python
#!/usr/bin/env python3
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"""
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Calculate QA Metrics
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Analyzes TEST-EXECUTION-TRACKING.csv and generates quality metrics.
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Usage:
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python scripts/calculate_metrics.py <tracking-csv-path>
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"""
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import sys
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import csv
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from pathlib import Path
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from collections import Counter
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def calculate_metrics(csv_path):
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"""Calculate comprehensive QA metrics from tracking CSV."""
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with open(csv_path, 'r') as f:
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reader = csv.DictReader(f)
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tests = list(reader)
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total = len([t for t in tests if t['Test Case ID'] not in ['', 'Test Case ID']])
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executed = len([t for t in tests if t['Status'] == 'Completed'])
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passed = len([t for t in tests if t['Result'] == '✅ PASSED'])
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failed = len([t for t in tests if t['Result'] == '❌ FAILED'])
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pass_rate = (passed / executed * 100) if executed > 0 else 0
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execution_rate = (executed / total * 100) if total > 0 else 0
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# Bug analysis
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bug_ids = [t['Bug ID'] for t in tests if t['Bug ID'] and t['Bug ID'] != '']
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unique_bugs = len(set(bug_ids))
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# Priority analysis
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priority_counts = Counter([t['Priority'] for t in tests if t['Priority']])
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print(f"\n{'='*60}")
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print(f"QA METRICS DASHBOARD")
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print(f"{'='*60}\n")
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print(f"📊 TEST EXECUTION")
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print(f" Total Tests: {total}")
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print(f" Executed: {executed} ({execution_rate:.1f}%)")
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print(f" Not Started: {total - executed}\n")
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print(f"✅ TEST RESULTS")
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print(f" Passed: {passed}")
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print(f" Failed: {failed}")
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print(f" Pass Rate: {pass_rate:.1f}%\n")
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print(f"🐛 BUG ANALYSIS")
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print(f" Unique Bugs: {unique_bugs}")
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print(f" Total Failures: {failed}\n")
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print(f"⭐ PRIORITY BREAKDOWN")
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for priority in ['P0', 'P1', 'P2', 'P3']:
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count = priority_counts.get(priority, 0)
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print(f" {priority}: {count}")
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print(f"\n🎯 QUALITY GATES")
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gates = {
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"Test Execution ≥100%": execution_rate >= 100,
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"Pass Rate ≥80%": pass_rate >= 80,
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"P0 Bugs = 0": len([t for t in tests if t['Bug ID'].startswith('BUG') and 'P0' in t['Notes']]) == 0,
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}
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for gate, status in gates.items():
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symbol = "✅" if status else "❌"
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print(f" {symbol} {gate}")
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print(f"\n{'='*60}\n")
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return {
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'total': total,
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'executed': executed,
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'passed': passed,
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'failed': failed,
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'pass_rate': pass_rate,
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'execution_rate': execution_rate,
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'unique_bugs': unique_bugs
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}
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print("Usage: python calculate_metrics.py <tracking-csv-path>")
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sys.exit(1)
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csv_path = Path(sys.argv[1])
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if not csv_path.exists():
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print(f"❌ Error: File not found: {csv_path}")
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sys.exit(1)
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calculate_metrics(csv_path)
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