The subagent was only reading text descriptions about images instead of
actually using the read tool on image files. This caused poor quality
reproductions based on guessed data rather than visual analysis.
Changes:
- Add CRITICAL instruction to use read tool on each image file
- Add Step 4: Verification step to compare generated vs original
- Add 'Extracting Data from Images' section with specific guidance
- Update guidelines to emphasize visual over textual extraction
- Allow scipy dependency for interpolation
Major changes:
- paper-image-extractor: Generate reference_plots.py for visual verification
- paper-director: Add image understanding checkpoint with side-by-side comparison
- paper-analyzer: Add data source labeling with reliability levels
- code-writer: Change from TDD to VDD (Verification-Driven Development)
- test-runner: Generate comparison reports with images and explanations
- verification skill: Add difference classification system
- code-generation skill: Emphasize result independence
Key principles:
- Code results are authoritative, paper values are references
- Differences are expected and documented, not bugs to fix
- Visual comparison prioritized over exact numerical match
- Tests verify sanity (shape, gradient, range), not exact values
