Systematic Debugging
SkillCloud & infraAdds a systematic debugging Claude skill that guides your agent to find a bug's root cause before applying any fix.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Systematic Debugging skill
About this skill
Structured debugging methodology, use before proposing fixes for any error or failure. Covers: code bugs, build errors, deploy failures, config conflicts, dependency issues, infra problems. Also use when previous fix attempts failed or root cause is unclear.
What this skill tells your AI
The instructions your AI receives, as published by sangrokjung/claude-forge in skills/systematic-debugging/SKILL.md and read by ahel’s review.
Overview
Guessing fixes wastes time and creates new bugs. Quick patches hide root problems.
Core principle: Never fix before finding the root cause. Symptom fixing is failure.
Iron Law
Never propose a fix without root cause investigation.
Phase 0 or Phase 1 must be completed before any fix is proposed. Phase 0 fixes are ONLY allowed when ALL of these are true:
- External research found an official solution or known issue for this exact error
- Change is single file, single point (config value, import, typo)
- No logic changes
When to Use
All technical problems:
- Test failures, build errors, deploy errors
- Config conflicts, dependency issues
- Infrastructure/environment problems
- Unexpected behavior, performance issues
Especially when:
- Under time pressure (urgency breeds guessing)
- "Let me just quickly fix this" comes to mind
- Multiple fix attempts have already been tried
- Previous fixes didn't work
- You don't fully understand the problem
The Phases
Each Phase must complete before proceeding to the next.
Phase 0: Quick Assessment
Run immediately when an error occurs. Before any fix attempt.
-
Classify the error — read the error message/symptoms:
- Same code works in different environment? → Environment issue
- After recent dependency/version change? → Dependency issue
- Only fails in specific code path? → Code issue
-
External research (exact match, 5 min max) — check official docs and GitHub Issues for known issues. Don't rely on self-knowledge alone.
- See:
references/external-research-guide.md
- See:
-
Branch decision:
- All Iron Law conditions met → Fix in Phase 0
- Any condition unmet → Enter Phase 1 full process
- Phase 0 quick-fix fails: Undo (git checkout/undo), enter Phase 1. This attempt counts in the fix counter.
Phase 1: Root Cause Investigation
Before any fix attempt:
-
Read the error carefully
- Don't skip errors/warnings
- Read the entire stack trace
- Record line numbers, file paths, error codes
-
Reproduce consistently
- Get exact reproduction steps
- Every time? If intermittent, collect more data
-
Check recent changes
- git diff, recent commits
- New dependencies, config changes
- Environment differences (env vars, Node/runtime version, OS)
-
Research external sources (deep read)
- Based on Phase 0 exact match results, investigate further
- Read official docs for the failure mechanism
- Check release notes for breaking changes
- See:
references/external-research-guide.md
-
Collect evidence in multi-component systems
- Log data in/out at each component boundary
- Run once to find where it breaks
- Then deep-dive into that component
-
Trace data flow
- Where does the wrong value originate?
- Trace the call stack backwards to the source
- See:
references/root-cause-tracing.md
Phase 2: Pattern Analysis
- Find similar working code in the same codebase
- Compare with reference implementations — read the full reference docs, don't skim
- Identify all differences between working and broken — don't assume "that's irrelevant"
- Map dependencies — what config, environment, other components are needed
Phase 3: Hypothesis and Testing
Before entering Phase 3:
- Verify clean state (git status)
- If not clean: git stash or save checkpoint
- On hypothesis failure: rollback to safe point, try new hypothesis (no cumulative fixes)
- Form a single hypothesis: "X is the root cause because Y" — specific, not vague
- Test minimally: smallest change to verify the hypothesis. One variable at a time.
- Verify before proceeding:
- Success → Phase 4
- Failure → New hypothesis (don't stack fixes on top of failed ones)
Phase 4: Implementation
- Write a failing test — simplest reproduction, automated if possible, before fixing
- Apply a single fix — only the identified root cause, one change at a time, no "while I'm at it"
- Verify the fix — test passes? No other tests broken? Problem actually resolved?
- If fix doesn't work:
- How many fix attempts so far?
- Under 3: return to Phase 1 with new information
- 3 or more: proceed to Phase 4.5
Phase 4.5: Architecture Question
Pattern of 3+ failed fixes:
- Each fix reveals new problems elsewhere
- Fix requires "major refactoring"
- Each fix creates symptoms in other places
Stop immediately and ask fundamental questions:
- Is this pattern itself sound?
- Are we clinging to it out of inertia?
- Should we refactor the architecture instead of fixing symptoms?
Report to user and discuss before any more fix attempts.
Red Flags — If you think this, STOP
- "Let me quickly fix it and investigate later"
- "Let me try changing X and see if it works"
- "Let me bundle multiple changes and test once"
- "Skip tests, just check manually"
- "It's probably X, let me fix it"
- "I don't fully understand but this might work"
- "Let me just try one more fix" (after 2+ attempts)
- "I don't need to check external docs for this one"
- "This is definitely a code issue" (without checking environment)
Any of the above: STOP. Return to Phase 0/1. 3+ fix failures: Architecture Question (Phase 4.5)
Common Rationalizations
| Excuse | Reality |
|---|---|
| "Simple problem, don't need the process" | Simple problems have root causes too. The process is fast for simple bugs. |
| "Too urgent for process" | Systematic debugging is faster than guessing. |
| "Let me try this first, then investigate" | First fix sets the pattern. Start right. |
| "I'll write tests after fixing" | Fixes without tests don't last. Test first. |
| "Bundle changes to save time" | Can't tell what worked. Creates new bugs. |
| "Docs are too long, I'll wing it" | Partial understanding = guaranteed bugs. Read it all. |
| "I can see the problem, just fix it" | Seeing symptoms ≠ understanding root cause. |
| "One more fix" (2+ failures) | 3+ failures = architecture problem. Ask, don't fix. |
| "I know this error, no need to check docs" | LLM confidence ≠ accuracy. Verify externally. |
Supporting Techniques
See references in this directory:
references/external-research-guide.md— External docs/GitHub Issues lookup procedurereferences/root-cause-tracing.md— Call stack backtracing to find bug origins
Quick Reference
| Phase | Key Activity | Success Criteria |
|---|---|---|
| 0. Quick Assessment | Error classification, external research (exact match) | Error type classified + 1+ external search done |
| 1. Root Cause | Read errors, reproduce, check changes, deep research | Understand what breaks and why |
| 2. Pattern | Find working similar code, compare | Differences identified |
| 3. Hypothesis | Single hypothesis, minimal test | Confirmed or new hypothesis |
| 4. Implementation | Write test, fix, verify | Bug fixed, tests pass |
| 4.5. Architecture | Stop after 3 failures, report | Architecture review decision |
Signals
- GitHub stars
- 843
- Forks
- 181
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
systematic-debugging-sangrokjung- Source
- github.com/sangrokjung/claude-forge
github.com/sangrokjung/claude-forge