
Debug Like Expert
When standard troubleshooting fails and you need to actually understand what's broken, this activates a methodical investigation protocol. It scans your project to detect the domain (Python, Rust, Swift, Unity, etc.) and loads relevant expertise from modular skill files before you start debugging. The core principle is harsh but necessary: treat code you wrote with more skepticism than unfamiliar code, because your assumptions about how it should work blind you to how it actually works. Every hypothesis gets tested, every fix gets verified, no drive-by solutions. It includes hooks for MCP servers to pull API docs and known issues when you need external context.
- skills.sh installs
- 175
- GitHub stars
- 2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add glittercowboy/taches-cc-resources --skill debug-like-expert --agent claude-codeInstalls into .claude/skills of the current project.
Files
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.
<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"
Sponsors
Details
- Repository
- github.com/glittercowboy/taches-cc-resources
- Categories
- Testing & QA, Data Science & ML, Debugging
- First seen
- Jun 3, 2026