AI / GitHub Copilot CLI Fundamentals Interview Questions
What logging and diagnostic capabilities does GitHub Copilot CLI provide?
Copilot CLI provides several mechanisms for understanding what is happening during a session - from verbose logging to dry-run previews - useful for debugging, auditing, and understanding agent behaviour.
# Enable verbose/debug logging copilot --log-level debug # Write logs to a file copilot --log-file ./copilot-debug.log # Non-interactive with logging copilot -p "explain this code" --log-level debug -s # Check version and build info copilot --version # Use /chronicle for session-level history and insights /chronicle "Show me everything Copilot did in the last session" "What tools did Copilot use during this session?"
| Option | Purpose |
|---|---|
| --log-level debug | Verbose output showing tool calls, API requests, decision logic |
| --log-file | Write log output to a file instead of (or in addition to) stdout |
| --version | Print the installed Copilot CLI version |
| /chronicle | Query past sessions, view what was done, get usage patterns |
| copilot -p ... -s | Non-interactive with clean output - useful for scripted diagnostics |
Debug logging is particularly useful when Copilot CLI is not behaving as expected - it shows what tools were called, what inputs they received, and what the model decided at each step, giving full visibility into the agent's reasoning loop.
What log level flag provides the most verbose output for debugging Copilot CLI behaviour?
Where would you look to understand what Copilot CLI did in a past session - specifically which tools it used and what actions it took?
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