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claude-memory/graph/solutions/bestiary-pdf-extraction-workflow-ba57b5.md
Cal Corum b140d4d82a migrate: 313 memories from MemoryGraph 
- 313 new markdown files created
- 30 relationships embedded
- 313 entries indexed
- State initialized with usage data
2026-02-13 11:11:48 -06:00

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id type title tags importance confidence created updated
ba57b560-92e1-4b6a-91b9-fb690ac44c96 solution Bestiary PDF extraction workflow
vagabond-rpg
foundryvtt
pdf-extraction
bestiary
python
0.7 0.8 2025-12-18T19:28:22.217828+00:00 2025-12-18T19:28:22.217828+00:00

Extracted 143 new creatures from Vagabond RPG PDF using pdftotext -raw and custom Python parser. Key learnings: 1) pdftotext -raw produces cleaner output than -layout for two-column PDFs, 2) Actor compendiums need _key prefix !actors! not !items!, 3) ID collisions handled with numeric suffixes, 4) Basic stats (HD, HP, TL, Speed, Armor, Morale, Zone) parse reliably, actions/abilities captured as raw text for manual refinement.