Code Quality errors

Code quality failures occur when the review workflow can't analyze your code or when the specialized subagents encounter problems during execution.

Common error signatures

FileNotFoundError: [Errno 2] No such file or directory — The specified path doesn't exist or isn't accessible
PermissionError: [Errno 13] Permission denied — Can't read the target files or directory
WorkflowExecutionError — One or more subagents (security-reviewer, quality-reviewer, perf-reviewer, architect-reviewer) failed to complete
ValueError: Invalid path format — The path argument is malformed or points to an unsupported file type
TimeoutError — Review took longer than expected, often on large codebases

Errors typically start in the CodeReviewWorkflow class when:

Path validation fails — The execute() method can't locate or access your specified files
Subagent coordination breaks — One of the four specialized reviewers (security, quality, performance, architecture) encounters an error and can't complete its analysis
Result synthesis fails — The workflow can't merge findings from all subagents into a unified report

Check the CodeReviewWorkflow.execute() method first, as it orchestrates the entire review process.

Verify your path exists and is readable. Run ls -la <your-path> to confirm the files exist and you have read permissions. Code quality needs to traverse the directory structure and read source files.
Check for unsupported file types. If your directory contains binary files, large data files, or non-source code, the subagents may fail. Try reviewing a smaller, source-code-only subset first.
Look for subagent-specific failures. The error message often indicates which reviewer failed — security-reviewer, quality-reviewer, perf-reviewer, or architect-reviewer. This narrows down whether it's a parsing issue, analysis complexity, or resource constraint.
Test with a minimal case. If reviewing a large codebase fails, try a single file first: /code-quality src/config.py. If that works, gradually increase scope to isolate where the failure occurs.
Check available memory and disk space. Deep reviews of large codebases can be resource-intensive. The workflow may fail if system resources are exhausted during analysis.

Tags: review, quality, bugs