systematic-debugging
Systematic Debugging provides a structured five-step debugging methodology for diagnosing and fixing errors: Reproduce, Isolate, Diagnose, Fix, and Verify. Use this skill when encountering bugs in code to ensure thorough error investigation rather than guess-and-check approaches, with specific guidance on reading error messages, adding minimal instrumentation, identifying root causes, and testing solutions across multiple inputs and edge cases.
git clone --depth 1 https://github.com/vstorm-co/pydantic-deepagents /tmp/systematic-debugging && cp -r /tmp/systematic-debugging/pydantic_deep/bundled_skills/systematic-debugging ~/.claude/skills/systematic-debuggingSKILL.md
# Systematic Debugging
A structured approach to finding and fixing bugs.
## The Debugging Loop
```
1. REPRODUCE → 2. ISOLATE → 3. DIAGNOSE → 4. FIX → 5. VERIFY
```
Never skip steps. Never guess-and-check repeatedly.
## Step 1: Reproduce
- Run the exact command that fails
- Capture FULL output (stdout AND stderr)
- Note: exit code, error message, stack trace
- If intermittent, identify what changes between runs
## Step 2: Isolate
- What's the MINIMAL input that triggers the error?
- Which specific line/function fails? (read the traceback bottom-up)
- Is it a compile error, runtime error, or wrong output?
- Does it fail on all inputs or specific ones?
## Step 3: Diagnose
### Read the error message carefully
| Error type | Where to look |
|-----------|---------------|
| Compile error | The FIRST error (later ones are often cascading) |
| Segfault | Last function in the stack trace, check array bounds and null pointers |
| Python traceback | The innermost frame (bottom), but also check the middle for context |
| Wrong output | Diff expected vs actual: `diff <(expected) <(actual)` |
| Timeout/hang | Is it an infinite loop? Deadlock? I/O bound? Add a timer or counter |
### Add minimal instrumentation
- C: `fprintf(stderr, "reached checkpoint %d\n", __LINE__);`
- Python: `print(f"DEBUG: {var=}", file=sys.stderr)`
- Check intermediate values, not just final output
- Remove debug prints after fixing
## Step 4: Fix
- Change ONE thing at a time
- If the same approach fails 3 times → completely different strategy
- Don't add workarounds — fix the root cause
- Common root causes:
- Off-by-one errors (loop bounds, array indexing)
- Type mismatches (int vs float, signed vs unsigned)
- Encoding issues (UTF-8 vs bytes)
- Path errors (relative vs absolute, missing trailing slash)
- Race conditions (file not written yet, process not started)
## Step 5: Verify
- Run the same command that failed before
- Test with multiple inputs, not just the one that was failing
- Check edge cases: empty input, single element, very large input
- Run any existing test suite
## Common Failure Patterns
### "It compiles but gives wrong output"
1. Print all intermediate values
2. Compare with a known-correct reference implementation
3. Check: integer overflow, floating point precision, endianness
### "It works on small input but times out on large"
1. Check algorithm complexity — O(n²) on 1M items = timeout
2. Profile: which loop/function takes the most time?
3. Restructure: hash maps, sorting, streaming
### "It works locally but fails in the test"
1. Check: absolute vs relative paths
2. Check: different working directory
3. Check: different input format than expected
4. Read the test script to understand what it actually checksBuilding, compiling, and resolving dependency issues across languages
Systematic code review for bugs, security, style, and performance
Working with diverse data formats: binary, text, structured, and custom
Systematic exploration of unknown environments before starting work
Git operations: commits, branches, PRs, and conflict resolution
Writing efficient code that handles large data and tight constraints
Refactor code to improve structure and maintainability
Create new reusable skills from conversation context