Analyze structured logs to reveal code execution paths and error origins.
npx skills add https://github.com/ewanyuan/cox-coding --skill code-observer
Please help me install this Agent Skill. Skill: code-observer Source: https://github.com/ewanyuan/cox-coding/tree/main/cn/code-observer Command: npx skills add https://github.com/ewanyuan/cox-coding --skill code-observer
Code path tracing and debugging: It automatically reveals how code executes, showing which functions run and where slowdowns or errors occur, so you can understand runtime behavior without stepping through with a debugger.
To start a full trace: provide the path to your observability logs and run the tracing pipeline, e.g., "python3 scripts/parse_logs.py --log-file /path/to/log.json --output ./parsed_logs.json" then "python3 scripts/generate_trace_report.py --logs ./parsed_logs.json --output ./trace_report.md"
High-intent search queries and answers about installing and using this skill.
Tracing code execution from logs involves analyzing structured log data to reconstruct function call graphs and identify timing or error origins. This Skill parses observability logs to map runtime behavior and outputs a Markdown report detailing execution paths.
Analyzing slow performance paths requires correlating logs with Prometheus metrics and application status to pinpoint timing hotspots. This process identifies where time is spent during execution and isolates the specific functions causing performance degradation.
Locating error origins without a debugger is possible by analyzing structured logs and test metrics to identify where exceptions are raised. This Skill traces how errors propagate through the function call graph to reveal exact failure points.
No external dependencies are required to correlate application status with observability logs beyond Python 3. The Skill relies entirely on bundled scripts to process logs, project data, and metrics for diagnosing reliability issues.
To generate a trace report, parse structured logs using the bundled script to create an intermediate JSON file, then run the report generator script. This outputs a Markdown trace report containing actionable insights for debugging.
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