Initial commit: Hermes Agent Skills collection
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# Iterative Fix-Verify Loop for Presentation QA
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Pattern for achieving zero-defect presentations through repeated visual QA cycles.
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Derived from a 17-slide deck QA session (5 cycles, 6 issues → 0 issues).
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## The Loop
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```
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┌─────────────────────────────────────────┐
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│ 1. GENERATE → node main.js │
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│ 2. RENDER → soffice → pdftoppm │
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│ 3. BATCH QA → batch_vision_qa.py │
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│ 4. TARGETED → vision_analyze (deep) │
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│ 5. FIX → patch source files │
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│ 6. REPEAT 2-5 until ALL CLEAN │
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└─────────────────────────────────────────┘
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```
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## Cycle Progression (Real Example)
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| Cycle | Issues Found | Action | Remaining |
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|-------|-------------|--------|-----------|
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| 1 | 1 (batch) + 6 (targeted) | Fixed all 6 | 3 remaining |
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| 2 | 3 (targeted) | Fixed all 3 | 1 remaining |
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| 3 | 1 (targeted) | Fixed | 1 remaining |
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| 4 | 1 (targeted) | Fixed | 0 |
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| 5 | 0 (full batch) | Done | 0 ✅ |
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## Why Multiple Cycles Are Needed
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Fixes introduce new problems:
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- Moving a subtitle down to fix overlap may push it into content below
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- Enlarging a badge circle may overlap neighboring elements
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- Changing line color for visibility may reduce contrast with another element
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- Shortening a label to prevent wrapping may lose meaning
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**Never declare success after the first fix-and-verify.** Always re-render and re-QA.
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## Batch + Targeted Prompt Division
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### Batch Prompt (Tier 1 — Breadth)
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Generic, checks all slides quickly (~25s for 17 slides). Uses expanded 6-category prompt:
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overlap, overflow, contrast, layout, content, symbols.
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### Targeted Prompts (Tier 2 — Depth)
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Element-specific questions for slides with:
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- **Diagrams**: "Are the connecting lines visible? What color?"
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- **Badges/icons**: "Do the letters inside circles render correctly?"
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- **Tables**: "Are all cells populated? Any placeholder text?"
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- **Examples**: "Does the example value match the description?"
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- **Arrows/connectors**: "Do arrows render properly between elements?"
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## Efficiency Tips
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- Only re-render and re-QA slides that were changed (not the entire deck)
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- But ALWAYS do a full batch scan at the end to confirm no regressions
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- Batch QA via direct API calls is 10-20x faster than sequential vision_analyze calls
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- Save QA results to JSON for comparison between cycles
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