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@kenjudy kenjudy commented Dec 9, 2025

  • Created verify_analysis_report.py to regenerate all statistics from trace data
  • Supports optional --expected-values parameter for PASS/FAIL verification
  • Full test coverage (16 tests) with mocked analysis functions
  • Type-safe implementation with mypy strict mode
  • All CI checks pass (black, ruff, mypy, bandit)
  • Updated README with usage documentation

Verification tool regenerates latency distribution, bottleneck analysis, and parallel execution metrics deterministically for audit purposes.

🤖 Generated with Claude Code

- Created verify_analysis_report.py to regenerate all statistics from trace data
- Supports optional --expected-values parameter for PASS/FAIL verification
- Full test coverage (16 tests) with mocked analysis functions
- Type-safe implementation with mypy strict mode
- All CI checks pass (black, ruff, mypy, bandit)
- Updated README with usage documentation

Verification tool regenerates latency distribution, bottleneck analysis,
and parallel execution metrics deterministically for audit purposes.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
@kenjudy kenjudy merged commit 570dea8 into main Dec 9, 2025
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github-actions bot commented Dec 9, 2025

📊 PR Metrics Analysis

Size Classification

LARGE (366 production lines)

Metric Value Target
Production files changed 1 -
Test files changed 1 -
Production lines added 366 <200 for easy review
Test lines added 560 -
Test-to-production ratio 1.53 0.5-2.0

Commit Quality

1 commits analyzed

Metric Count % Target
Large commits (>100 lines) 1 100% <20%
Sprawling commits (>5 files) 0 0% <10%

Recommendations

  • ⚠️ Large PR: This may take longer to review. Consider incremental changes in future.
  • ⚠️ High % of large commits: Aim for smaller, atomic commits

Automated analysis via PDCA Framework

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2 participants