thor-db

Analyze THOR SQLite database timing data by running Python scripts like thor_db_top_times.py on thor10.db or thor11.db to query the times table and identify long-running rules or modules. This pinpoints slow scan elements for targeted optimization.

Diagnose slow THOR scans by inspecting timing telemetry stored in the internal SQLite database. Use thor_db_slow_rules_hint.py to review slow rules and export summaries, enabling you to optimize rule processing and debug performance hotspots effectively.

Evaluate resume markers and delta data in thor10.db or thor11.db by querying the stats and tbl tables via Python's sqlite3 interface. This reveals interruption points and highlights improvements across multiple THOR scan runs.

No external dependencies are required to query ThorDB for performance diagnostics. The Skill relies solely on Python's built-in sqlite3 interface to access thor10.db and thor11.db, exposing timing and stats results via CLI-friendly outputs.

Compare THOR performance telemetry across different scan runs by analyzing delta data stored in the SQLite database. The Skill evaluates resume markers and timing stats to show improvements and interruptions between thor10.db and thor11.db sessions.

Limitations of analyzing THOR timing data include its strict scope of thor10.db and thor11.db files. It focuses on performance, resume state, and delta comparisons, meaning it cannot diagnose external system latency or network-related scan delays outside the SQLite telemetry.