What problem does it solve? Python codebases often accumulate try/except blocks that are too broad, catch the wrong exceptions, or silently swallow errors, making bugs hard to detect and debug. This Skill systematically reviews every try/except block and tightens exception handling so failures surface correctly. ## Core Features & Use Cases - Scope Analysis: Checks whether each try block contains only the operation that can actually raise the expected exception, moving setup and processing code out. - Exception Appropriateness Check: Flags cases where catching KeyError, AttributeError, or IndexError should be replaced with in, .get(), hasattr(), or length checks. - Handler Risk Ranking: Ranks except clauses from most to least dangerous (bare except, except Exception, tuples, specific types) and identifies handlers that mask failures via pass or default returns. - Use Case: Before merging a large Python pull request, run this audit to find a bare except: that was silently hiding database connection failures in production. ## Quick Start Ask the AI to audit all try/except blocks in your Python project and tighten each one so the try covers only the operation that can raise the expected exception.