justice-matrix-research

You can automate youth justice case discovery by invoking the /ralph-matrix-scan slash command, which triggers automated source scanning, AI extraction, and geocoding to update your research database with new global entries.

Automated source scanning is a scheduled research cycle that discovers global youth justice cases, performs AI data extraction and geocoding, categorizes entries, and feeds them into a review queue for admin approval pipeline integration.

Yes, this automated research workflow supports regional coverage analysis, cross-source mapping, and ongoing campaign monitoring by continuously discovering global youth justice cases and updating the database with categorized, geocoded entries.

No external dependencies or components are required to run cross-source mapping for youth justice advocacy, as the skill operates independently to execute source health checks, AI extraction, and database updates.

The best way to integrate discovered youth justice cases into an admin approval pipeline is through the built-in review queue, which automatically collects categorized, geocoded entries from the source scanning process for administrative review.

Your youth justice research workflow needs source health checks and coverage gap analysis to ensure automated discovery cycles maintain high data quality, identify missing regional sources, and prevent incomplete advocacy campaign tracking in the database.