Blackhole works by placing a hidden link that good crawlers follow the rules to avoid. Anything that ignores robots.txt and walks straight into the trap is recorded in the plugin's own table with the IP, host, request URI, user agent, and trap time. The settings screen lists the trapped bots and lets you ban them, which is exactly the right primitive, but the same screen cannot answer how many bots were trapped this week or which user-agent families dominate.

SleekView Charts reads the trap log as a normal data source. The ip, host, ua, and date columns from wp_blackhole_bots become groupable fields, ready for charting. A donut splits traps by user-agent family, a Number card shows the weekly total, a horizontal bar surfaces the top trapped IPs, and an area chart traces daily trap volume so scraper waves stand out before they hit a rate limit upstream.

Nothing is rewritten on Blackhole's side. The plugin keeps trapping and banning, the log keeps growing, and the dashboard renders the same rows in a shape that supports a daily anti-bot review on top of the row-level bans Blackhole already manages.

A bot trap makes a binary decision: the request followed the disallow rule, or it did not. Each trapped row is interesting once, then becomes one more line in a list. What a security team needs is the shape of those rows over a week, not the rows themselves.

The data exists in wp_blackhole_bots with all the columns the trap maintains. Rendering it as Number, Pie, Bar, and Area cards costs nothing on the writing side and turns the same rows into a dashboard. The cadence of anti-bot review shifts from incident-only to a daily glance, while the underlying trap stays untouched and ready for forensics whenever the next incident hits.