// Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework with built-in backward tracing for deep-stack failures, ensuring root-cause understanding before implementation
Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.
Look up documentation and source code for libraries and packages. Use when the user asks a question about a library, needs to understand a library's API, or when you need information about a library that you don't know about. Triggers on questions like "How do I use X library?", "What's the API for Y?", "Show me how Z library handles this", or when encountering unfamiliar library usage.
Use when updating CHANGELOG.md. Enforces consistent formatting with bolded item names, dash separators, and specific section ordering.
| name | debug |
| description | Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework with built-in backward tracing for deep-stack failures, ensuring root-cause understanding before implementation |
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
Violating the letter of this process is violating the spirit of debugging.
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
If you haven't completed Phase 1, you cannot propose fixes.
Use for ANY technical issue:
Use this ESPECIALLY when:
Don't skip when:
You MUST complete each phase before proceeding to the next.
BEFORE attempting ANY fix:
Read Error Messages Carefully
Reproduce Consistently
Check Recent Changes
Gather Evidence in Multi-Component Systems
WHEN system has multiple components (CI → build → signing, API → service → database):
BEFORE proposing fixes, add diagnostic instrumentation:
For EACH component boundary:
- Log what data enters component
- Log what data exits component
- Verify environment/config propagation
- Check state at each layer
Run once to gather evidence showing WHERE it breaks
THEN analyze evidence to identify failing component
THEN investigate that specific component
Example (multi-layer system):
# Layer 1: Workflow
echo "=== Secrets available in workflow: ==="
echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"
# Layer 2: Build script
echo "=== Env vars in build script: ==="
env | grep IDENTITY || echo "IDENTITY not in environment"
# Layer 3: Signing script
echo "=== Keychain state: ==="
security list-keychains
security find-identity -v
# Layer 4: Actual signing
codesign --sign "$IDENTITY" --verbose=4 "$APP"
This reveals: Which layer fails (secrets → workflow ✓, workflow → build ✗)
Trace Data Flow
WHEN error is deep in call stack:
Use built-in backward tracing:
Use this when the bug appears far away from the real trigger.
Typical signals:
Tracing process:
Mini example:
await execFileAsync("git", ["init"], { cwd: projectDir });
git init runs in the wrong directoryprojectDir?projectDir come from?When manual tracing stalls, add instrumentation before the dangerous operation:
async function gitInit(directory: string) {
const stack = new Error().stack;
console.error("DEBUG git init:", {
directory,
cwd: process.cwd(),
nodeEnv: process.env.NODE_ENV,
stack,
});
await execFileAsync("git", ["init"], { cwd: directory });
}
Tracing rule: never stop at "this line crashed." Keep going until you can say which caller, input, or state transition created the bad value.
Find the pattern before fixing:
Find Working Examples
Compare Against References
Identify Differences
Understand Dependencies
Scientific method:
Form Single Hypothesis
Test Minimally
Verify Before Continuing
When You Don't Know
Fix the root cause, not the symptom:
Decide on Testing Strategy
Auto-decide based on complexity:
If writing test:
If skipping test:
Implement Single Fix
Verify Fix
If test was written:
If no test:
Always check:
If Fix Doesn't Work
If 3+ Fixes Failed: Question Architecture
Pattern indicating architectural problem:
STOP and question fundamentals:
Discuss with your human partner before attempting more fixes
This is NOT a failed hypothesis - this is a wrong architecture.
If you catch yourself thinking:
ALL of these mean: STOP. Return to Phase 1.
If 3+ fixes failed: Question the architecture (see Phase 4.5)
Watch for these redirections:
When you see these: STOP. Return to Phase 1.
| Excuse | Reality |
|---|---|
| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |
| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |
| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |
| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |
| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |
| "UI fix doesn't need tests" | Correct! UI components verified via typecheck/manual testing, not unit tests. |
| Phase | Key Activities | Success Criteria |
|---|---|---|
| 1. Root Cause | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY |
| 2. Pattern | Find working examples, compare | Identify differences |
| 3. Hypothesis | Form theory, test minimally | Confirmed or new hypothesis |
| 4. Implementation | Create test, fix, verify | Bug resolved, tests pass |
If systematic investigation reveals issue is truly environmental, timing-dependent, or external:
But: 95% of "no root cause" cases are incomplete investigation.
Testing skills (when needed):
From debugging sessions: