pihole-blocklist

Evaluating a Pi-hole blocklist involves checking category fit, quality signals, format compatibility, and operational risk to identify false positives. This structured assessment ensures your curated blocklist index avoids introducing unnecessary blocking errors.

Blocklist curation taxonomy assigns exactly one primary category to each Pi-hole source to maintain consistency. You need this structured evaluation when adding new ad, tracker, or malware sources to keep your blocklist entries organized and discoverable.

Checking Pi-hole format compatibility involves verifying raw URL availability and distinguishing between hosts file formatting and plain domain lists. This readiness check ensures the blocklist source can be parsed correctly without operational failures.

Yes, blocklist evaluation generates repo-ready documentation by producing a structured assessment with category, overlap risk, and recommendation fields. This curation-oriented output is suitable for committing updates directly to your blocklist index.

Automated Pi-hole blocklist assessment is limited by its strict avoidance of fabricating missing facts. It cannot evaluate sources lacking clear operational metadata or formatting signals, meaning it requires transparent data to assign accurate category and overlap risk.