4-phase root cause process + passive behavior auto-detection + L1→L4 pressure escalation (includes root-cause-tracing, defense-in-depth, condition-based-waiting techniques)
Installation
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4-phase root cause process + passive behavior auto-detection + L1→L4 pressure escalation (includes root-cause-tracing, defense-in-depth, condition-based-waiting techniques)
Systematic Debugging
Overview
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.
The Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
If you haven't completed Phase 1, you cannot propose fixes.
When to Use
Use for ANY technical issue:
Test failures
Bugs in production
Unexpected behavior
Performance problems
Build failures
Integration issues
Use this ESPECIALLY when:
Under time pressure (emergencies make guessing tempting)
"Just one quick fix" seems obvious
You've already tried multiple fixes
Previous fix didn't work
You don't fully understand the issue
Don't skip when:
Issue seems simple (simple bugs have root causes too)
You're in a hurry (rushing guarantees rework)
Manager wants it fixed NOW (systematic is faster than thrashing)
The Four Phases
You MUST complete each phase before proceeding to the next.
Phase 1: Root Cause Investigation
BEFORE attempting ANY fix:
Read Error Messages Carefully
Don't skip past errors or warnings
They often contain the exact solution
Read stack traces completely
Note line numbers, file paths, error codes
Reproduce Consistently
Can you trigger it reliably?
What are the exact steps?
Does it happen every time?
If not reproducible → gather more data, don't guess
Check Recent Changes
What changed that could cause this?
Git diff, recent commits
New dependencies, config changes
Environmental differences
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: Workflowecho"=== Secrets available in workflow: ==="echo"IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"# Layer 2: Build scriptecho"=== Env vars in build script: ==="env | grep IDENTITY || echo"IDENTITY not in environment"# Layer 3: Signing scriptecho"=== 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:
See root-cause-tracing.md in this directory for the complete backward tracing technique.
Quick version:
Where does bad value originate?
What called this with bad value?
Keep tracing up until you find the source
Fix at source, not at symptom
Phase 2: Pattern Analysis
Find the pattern before fixing:
Find Working Examples
Locate similar working code in same codebase
What works that's similar to what's broken?
Compare Against References
If implementing pattern, read reference implementation COMPLETELY
Don't skim - read every line
Understand the pattern fully before applying
Identify Differences
What's different between working and broken?
List every difference, however small
Don't assume "that can't matter"
Understand Dependencies
What other components does this need?
What settings, config, environment?
What assumptions does it make?
Phase 3: Hypothesis and Testing
Scientific method:
Form Single Hypothesis
State clearly: "I think X is the root cause because Y"
Write it down
Be specific, not vague
Test Minimally
Make the SMALLEST possible change to test hypothesis
One variable at a time
Don't fix multiple things at once
Verify Before Continuing
Did it work? Yes → Phase 4
Didn't work? Form NEW hypothesis
DON'T add more fixes on top
When You Don't Know
Say "I don't understand X"
Don't pretend to know
Ask for help
Research more
Phase 4: Implementation
Fix the root cause, not the symptom:
Create Failing Test Case
Simplest possible reproduction
Automated test if possible
One-off test script if no framework
MUST have before fixing
Use the superpowers:test-driven-development skill for writing proper failing tests
Implement Single Fix
Address the root cause identified
ONE change at a time
No "while I'm here" improvements
No bundled refactoring
Verify Fix
Test passes now?
No other tests broken?
Issue actually resolved?
If Fix Doesn't Work
STOP
Count: How many fixes have you tried?
If < 3: Return to Phase 1, re-analyze with new information
If ≥ 3: STOP and question the architecture (step 5 below)
DON'T attempt Fix #4 without architectural discussion
If 3+ Fixes Failed: Question Architecture
Pattern indicating architectural problem:
Each fix reveals new shared state/coupling/problem in different place
Fixes require "massive refactoring" to implement
Each fix creates new symptoms elsewhere
STOP and question fundamentals:
Is this pattern fundamentally sound?
Are we "sticking with it through sheer inertia"?
Should we refactor architecture vs. continue fixing symptoms?
Discuss with your human partner before attempting more fixes
This is NOT a failed hypothesis - this is a wrong architecture.
Red Flags - STOP and Follow Process
If you catch yourself thinking:
"Quick fix for now, investigate later"
"Just try changing X and see if it works"
"Add multiple changes, run tests"
"Skip the test, I'll manually verify"
"It's probably X, let me fix that"
"I don't fully understand but this might work"
"Pattern says X but I'll adapt it differently"
"Here are the main problems: [lists fixes without investigation]"
Proposing solutions before tracing data flow
"One more fix attempt" (when already tried 2+)
Each fix reveals new problem in different place
ALL of these mean: STOP. Return to Phase 1.
If 3+ fixes failed: Question the architecture (see Phase 4.5)
🔍 Passive Behavior Detection (Auto-Trigger)
Inspired by PUA (8.5K⭐). The 4 phases above tell you HOW to debug.
This section makes sure you actually DO it — by detecting avoidance patterns.
This skill auto-activates when ANY of the following patterns are detected:
Giving Up & Deflecting
About to say "I cannot" / "I'm unable to solve" / "This is beyond my capabilities"
Says "This is out of scope" / "Needs manual handling"
Pushes the problem to user: "Please check..." / "I suggest manually..." / "You might need to..."
Blame-Shifting Without Verification
Blames environment without verifying: "Probably a permissions issue" / "Probably a network issue"
Claims "This API doesn't support it" without reading docs
"This is beyond my knowledge cutoff" (you have search tools — use them)
Busywork Spinning
Repeatedly tweaking the same code/parameters without producing new information
Fixes surface issue and stops — doesn't check related issues
Skips verification, claims "done" without evidence
Passive Waiting
Stops after fixing, waits for user instructions instead of proactively investigating
Only answers questions without solving problems
Encounters auth/network/permission errors and gives up without trying alternatives
Gives advice instead of code/commands
User Frustration Signals (multi-language)
"why does this still not work" / "try harder" / "try again"
When detected → immediately enter Pressure Escalation below.
Does NOT trigger: First-attempt failures, known fix already executing.
⚡ Pressure Escalation (L1 → L4)
The number of consecutive failures determines escalation level. Each level comes with mandatory actions — you MUST complete them before continuing.
Attempt
Level
Mandatory Actions
2nd
L1 — Verbal Warning
Stop current approach. Switch to a fundamentally different solution path. Do NOT tweak the same thing again.
3rd
L2 — Written Feedback
① Search the complete error message with tools. ② Read relevant source code (not just the error line — 50 lines of context). ③ List 3 fundamentally different hypotheses and test each.
4th
L3 — Formal Rescue
Complete ALL 7 items on the Rescue Checklist below. List 3 entirely new hypotheses and verify each one.
5th+
L4 — Last Resort
Desperation mode: minimal PoC in isolated environment. Consider completely different tech stack/approach. If still failing → stop and escalate to human.
7-Point Rescue Checklist (mandatory for L3+)
When L3 or above is triggered, you MUST complete and report on every item:
Read failure signals word by word — Did you read the full error text? Not just the first line — the ENTIRE message, stack trace, and any warnings above it.
Proactive search — Did you use tools to search the exact error text? Multi-angle keywords? Official documentation?
Read raw context — Did you read 50+ lines of source around the failure point? Not just the error line.
Verify underlying assumptions — Did you confirm ALL assumptions with tools? (versions, paths, dependencies, API behavior, env vars)
Invert assumptions — Did you try the EXACT OPPOSITE hypothesis from your current direction?
Minimal isolation — Can you reproduce the problem in the smallest possible scope? (minimal repro script, single API call, one-line test)
Change direction — Did you switch tools, methods, angles, or frameworks? (Not switching parameters — switching your THINKING)
Anti-Rationalization Table
These excuses are blocked. Using any of them triggers the corresponding escalation.
Your Excuse
Reality
Triggers
"This is beyond my capabilities"
You have search, file reading, and command execution tools. Exhaust them first.
L1
"I suggest the user handle this manually"
That's deflection, not a solution. This is your problem to solve.
L3
"I've already tried everything"
Did you search? Read source? Complete the checklist? "Everything" without evidence is feelings.
L2
"It's probably an environment issue"
Did you VERIFY that? Unverified attribution is blame-shifting.
L2
"I need more context"
You have tools. Investigate first, ask only what truly requires human knowledge.
L2
"This API doesn't support it"
Did you read the docs? Actually verify?
L2
Repeatedly tweaking same code
That's the definition of insanity. Switch to fundamentally different approach.
L1
"I cannot solve this problem"
Last chance. Complete the 7-Point Rescue Checklist before making that claim.
L4
Claims "done" without verification
Where's the evidence? Run build/test/curl yourself. Prove it.
L1
Waiting for user to tell next steps
Take initiative. What's the logical next step? Do it.
L1
Only giving advice, no code
Deliver solutions, not suggestions. Write the code, run the command.
L1
your human partner's Signals You're Doing It Wrong
Watch for these redirections:
"Is that not happening?" - You assumed without verifying
"Will it show us...?" - You should have added evidence gathering
"Stop guessing" - You're proposing fixes without understanding
"Ultrathink this" - Question fundamentals, not just symptoms
"We're stuck?" (frustrated) - Your approach isn't working
When you see these: STOP. Return to Phase 1.
Common Rationalizations
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.
"I'll write test after confirming fix works"
Untested fixes don't stick. Test first proves it.
"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.
