- Created 'nuclear_strip' helper to remove all hidden and unicode whitespace characters.
- Applied 'nuclear_strip' globally to the inventory and during content extraction.
- Fixed MD031 by ensuring proper blank line spacing around Mermaid code fences in introduction.md.
- Hardened comparison tables and link lists against invisible formatting issues.
- Implemented global data sanitization upon inventory load to strip whitespace and hidden characters from all titles.
- Forced whitespace stripping during the initial Markdown extraction phase (V1 content gathering).
- This ensures 100% clean link text across all rendered documentation, preventing 'Spaces inside link text' violations.
- Stripped all leading/trailing whitespace (including non-breaking spaces) from link titles in list items, comparison tables, and the index pulse.
- Ensured URLs are stripped to prevent formatting issues.
- This resolves the persistent 'Spaces inside link text' error in generated documentation.
- Fixed MD024: Included H1 main title in used_headers to prevent duplicate sub-headings.
- Fixed MD031: Added mandatory blank lines around Mermaid code fences in introduction.md.
- Fixed MD039: Stripped leading/trailing spaces from link titles to satisfy formatting rules.
- Fixed MD025: Ensured only one H1 heading exists per document by starting internal headings at H2.
- Fixed MD024: Implemented a header deduplication mechanism using a per-file 'used_headers' set.
- Improved structure: Properly nested hierarchies to satisfy strict Markdown standards.
- Fixed dark mode visibility by setting proper text and tag luminosities in docs/static/v2_elite.css.
- Eliminated triple 'Explore Related' blocks by moving the injection outside recursion in src/v2_optimizer.py.
- Fixed 'Technical Deep-Dive' rendering by correcting Markdown indentation for collapsible blocks.
- Added auto-save every 500 GitHub API fetches to prevent data loss on early cancellation.
- This ensures that subsequent runs skip already enriched repositories.
- Reduced BATCH_SIZE_FAST to 50 to prevent AI request timeouts.
- Hardened call_gemini_with_retry to strictly use Flash/Lite models when prefer_flash=True.
- Ensured newest model versions are prioritized within the Flash tier.
- Added periodic save (every 20 batches) to prevent data loss in long runs.
- Verified Flash-First settings (Batch: 100, Delay: 2s, prefer_flash=True).
- Transitioned V2 Optimizer to high-density batching (100 items/batch).
- Reconfigured Health Cleaner to use Flash/Lite for high-volume URL rescue.
- Codified mandates 48-50 in GEMINI.md for AI governance.
- Added Agentic Model Selection Matrix to README.md.
- Improved error handling to ensure Rate-Limit events trigger Circuit Breakers.
