Debug Like Expert

<objective> Deep analysis debugging mode for complex issues. This skill activates methodical investigation protocols with evidence gathering, hypothesis testing, and rigorous verification when standard troubleshooting has failed.

The skill emphasizes treating code you wrote with MORE skepticism than unfamiliar code, as cognitive biases about "how it should work" can blind you to actual implementation errors. Use scientific method to systematically identify root causes rather than applying quick fixes. </objective>

<context_scan> Run on every invocation to detect domain-specific debugging expertise:

# What files are we debugging?
echo "FILE_TYPES:"
find . -maxdepth 2 -type f 2>/dev/null | grep -E '\.(py|js|jsx|ts|tsx|rs|swift|c|cpp|go|java)$' | head -10

# Check for domain indicators
[ -f "package.json" ] && echo "DETECTED: JavaScript/Node project"
[ -f "Cargo.toml" ] && echo "DETECTED: Rust project"
[ -f "setup.py" ] || [ -f "pyproject.toml" ] && echo "DETECTED: Python project"
[ -f "*.xcodeproj" ] || [ -f "Package.swift" ] && echo "DETECTED: Swift/macOS project"
[ -f "go.mod" ] && echo "DETECTED: Go project"

# Scan for available domain expertise
echo "EXPERTISE_SKILLS:"
ls ~/.claude/skills/expertise/ 2>/dev/null | head -5

Present findings before starting investigation. </context_scan>

<domain_expertise> Domain-specific expertise lives in ~/.claude/skills/expertise/

Domain skills contain comprehensive knowledge including debugging, testing, performance, and common pitfalls. Before investigation, determine if domain expertise should be loaded.

<scan_domains>

ls ~/.claude/skills/expertise/ 2>/dev/null

This reveals available domain expertise (e.g., macos-apps, iphone-apps, python-games, unity-games).

If no expertise skills found: Proceed without domain expertise (graceful degradation). The skill works fine with general debugging methodology. </scan_domains>