log-cleanup-report

Server log disk usage is reduced by this Skill through inventorying file sizes and date ranges, then computing signal-to-noise metrics to generate actionable cleanup, rotation, and archiving recommendations.

Signal-to-noise analysis in log diagnostics separates meaningful signal lines from noise lines to compute ratios and detect adaptive logging, guiding which server logs are safe to trim or archive.

A log rotation and cleanup plan is created by running this Skill against IQRight server and web logs to parse file inventories, compute noise metrics, and output structured recommendations based on thresholds.

Yes, this log analysis works on both server and web logs by inventorying file names, sizes, line counts, and date ranges across both types to quantify disk usage and noise.

The best way to identify noise in server logs before archiving is computing signal-to-noise ratios and detecting adaptive logging status, which pinpoints exactly which files contain bloat and require cleanup.

No specific dependencies are required to parse log files for cleanup recommendations, as this Skill operates independently to compute signal-to-noise metrics and output structured archiving plans.