musmem-locations

To extract bodybuilding contest dates and venues, this Skill parses XML article notes and NPC scorecard listing pages, then normalizes the extracted contest names and locations using MuscleMemory conventions before appending them to a centralized JSON dataset.

Yes, you can scrape scorecard locations without data loss because the merge process is non-destructive, appending new contest dates and venues to contest_locations.json only after performing conflict checks and deduplication against existing entries.

The best way to build a contest location dataset spanning the 1940s to present is running prescreen_articles.py to scan articles and generate a manifest, then executing merge_locations.py to consolidate the extracted dates, venues, and locations into contest_locations.json.

Yes, the scraper supports merging data from both XML article files and scorecard listings by utilizing two distinct workflows that extract contest metadata and run conflict checks before performing a non-destructive merge into the centralized JSON file.

The prescreen_articles.py script works by scanning all provided historical articles to identify relevant bodybuilding contest data, generating a manifest of contest names, years, dates, venues, and locations that feed into the subsequent merge_locations.py consolidation step.