← ClaudeAtlas

debugginglisted

Systematically debug code issues using proven methodologies. Use when encountering errors, unexpected behavior, or performance problems. Handles error analysis, root cause identification, debugging strategies, and fix verification.
aiskillstore/marketplace · ★ 329 · Code & Development · score 82
Install: claude install-skill aiskillstore/marketplace
# Debugging ## When to use this skill - Encountering runtime errors or exceptions - Code produces unexpected output or behavior - Performance degradation or memory issues - Intermittent or hard-to-reproduce bugs - Understanding unfamiliar error messages - Post-incident analysis and prevention ## Instructions ### Step 1: Gather Information Collect all relevant context about the issue: **Error details**: - Full error message and stack trace - Error type (syntax, runtime, logic, etc.) - When did it start occurring? - Is it reproducible? **Environment**: - Language and version - Framework and dependencies - OS and runtime environment - Recent changes to code or config ```bash # Check recent changes git log --oneline -10 git diff HEAD~5 # Check dependency versions npm list --depth=0 # Node.js pip freeze # Python ``` ### Step 2: Reproduce the Issue Create a minimal, reproducible example: ```python # Bad: Vague description "The function sometimes fails" # Good: Specific reproduction steps """ 1. Call process_data() with input: {"id": None} 2. Error occurs: TypeError at line 45 3. Expected: Return empty dict 4. Actual: Raises exception """ # Minimal reproduction def test_reproduce_bug(): result = process_data({"id": None}) # Fails here assert result == {} ``` ### Step 3: Isolate the Problem Use binary search debugging to narrow down the issue: **Print/Log debugging**: ```python def problematic_function(data): print(f"[DEBUG] Input: {data}") #