Logging

Logging is needed for findings generation to trace data flow and identify failure points during findings creation. Logging is necessary when AgentFinding is created to verify that findings are saved and streamed to the frontend properly. Logging is associated with SQL extraction regex fix as it will be added to trace extraction and execution results. question_router logging is a specific logging to be added after SQL query execution to provide diagnostics. findings_generator logging is a specific logging to be added at the start of findings generation for diagnostics. agent.py logging is a specific logging to be added when creating AgentFinding records to confirm saving of findings. Skill Logging records are stored in the agent_skill_log database table capturing skill execution details. Logging will be added to question_router to trace execution after SQL query to help diagnose findings generation issues. Logging will be added to findings_generator at the start of generate_findings to monitor numeric columns detection and diagnose failure points. Logging will be added in agent.py when AgentFinding records are created to verify findings saving to the database. The Logging framework instruments agent_skills.py process_message() to capture errors and execution flow.