Query SQLite DAQ log errors with read-only SQL joins.
npx skills add https://github.com/carbonscott/deploy-opencode --skill daq-logs
Please help me install this Agent Skill. Skill: daq-logs Source: https://github.com/carbonscott/deploy-opencode/tree/main/claude/skills/daq-logs Command: npx skills add https://github.com/carbonscott/deploy-opencode --skill daq-logs
Quickly locate, analyze, and trace errors in the LCLS DAQ log database to diagnose issues and understand failure cascades.
Run a read-only SQL query to fetch recent errors for a given host and component and output results with headers.
High-intent search queries and answers about installing and using this skill.
Query LCLS DAQ logs by running read-only SELECT statements that join log_files and log_errors tables to trace error cascades by pulse_id. You can filter by host, component, or timestamp and order results to pinpoint root causes.
Investigate DAQ log errors in a SQLite database by executing SQL queries against the log_errors table. You can cross-reference host and component information, validate ingestion status across log_files, and export diagnostic results for further root-cause analysis.
Yes, you can use SQL to cross-reference host and component data for DAQ diagnostics. The Skill supports joining log_files and log_errors tables, allowing you to filter by specific hosts or components to validate ingestion status and isolate failures.
Validate ingestion status by running SELECT queries that join the log_files and log_errors tables. This approach lets you cross-reference file ingestion records with logged errors to identify missing data or processing failures within the DAQ pipeline.
Yes, the SQLite DAQ log query tool supports exporting diagnostic results. You can use ordering and limiting clauses to refine your SELECT query output, and export the retrieved error data to support debugging and root-cause analysis workflows.
Querying DAQ logs with SQL is limited to read-only SELECT statements. The Skill enforces this constraint to protect the SQLite database, meaning you cannot modify, insert, or delete log_files or log_errors records during diagnostic workflows.
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