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Systematic debugging

Skill ComeOnOliver/skillshub/skills/aiskillstore/marketplace/codingcossack/systematic-debugging

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npx -y skills add ComeOnOliver/skillshub --skill systematic-debugging

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What its author says it does

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Root cause analysis for debugging. Use when bugs, test failures, or unexpected behavior have non-obvious causes, or after multiple fix attempts have failed.

SKILL.md

4.5 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it

Systematic Debugging

Core principle: Find root cause before attempting fixes. Symptom fixes are failure.

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

  1. Read Error Messages Carefully

    • Read stack traces completely
    • Note line numbers, file paths, error codes
    • Don't skip warnings
  2. Reproduce Consistently

    • What are the exact steps?
    • If not reproducible β†’ gather more data, don't guess
  3. Check Recent Changes

    • Git diff, recent commits
    • New dependencies, config changes
    • Environmental differences
  4. Gather Evidence in Multi-Component Systems

    WHEN system has multiple components (CI β†’ build β†’ signing, API β†’ service β†’ database):

    Add diagnostic instrumentation before proposing fixes:

    For EACH component boundary:
      - Log what data enters/exits component
      - Verify environment/config propagation
      - Check state at each layer
    
    Run once to gather evidence β†’ analyze β†’ identify failing component
    

    Example:

    # Layer 1: Workflow
    echo "=== Secrets available: ==="
    echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"
    
    # Layer 2: Build script
    env | grep IDENTITY || echo "IDENTITY not in environment"
    
    # Layer 3: Signing
    security find-identity -v
    
  5. Trace Data Flow

    See references/root-cause-tracing.md for backward tracing technique.

    Quick version: Where does bad value originate? Trace up call chain until you find the source. Fix at source.

Phase 2: Pattern Analysis

  1. Find Working Examples - Similar working code in codebase
  2. Compare Against References - Read reference implementations COMPLETELY, don't skim
  3. Identify Differences - List every difference, don't assume "that can't matter"
  4. Understand Dependencies - Components, config, environment, assumptions

Phase 3: Hypothesis and Testing

  1. Form Single Hypothesis - "I think X is root cause because Y" - be specific
  2. Test Minimally - SMALLEST possible change, one variable at a time
  3. Verify - Worked β†’ Phase 4. Didn't work β†’ form NEW hypothesis, don't stack fixes
  4. When You Don't Know - Say so. Don't pretend.

Phase 4: Implementation

  1. Create Failing Test Case

    • Use the test-driven-development skill
    • MUST have before fixing
  2. Implement Single Fix

    • ONE change at a time
    • No "while I'm here" improvements
  3. Verify Fix

    • Test passes? Other tests still pass? Issue resolved?
  4. If Fix Doesn't Work

    • Count attempts
    • If < 3: Return to Phase 1 with new information
    • If β‰₯ 3: Escalate (below)

Escalation: 3+ Failed Fixes

Pattern indicating architectural problem:

  • Each fix reveals new problems elsewhere
  • Fixes require massive refactoring
  • Shared state/coupling keeps surfacing

Action: STOP. Question fundamentals:

  • Is this pattern fundamentally sound?
  • Are we continuing through inertia?
  • Refactor architecture vs. continue fixing symptoms?

Discuss with human partner before more fix attempts. This is wrong architecture, not failed hypothesis.

Red Flags β†’ STOP and Return to Phase 1

If you catch yourself thinking:

  • "Quick fix for now, investigate later"
  • "Just try changing X"
  • "I'll skip the test"
  • "It's probably X"
  • "Pattern says X but I'll adapt it differently"
  • Proposing solutions before tracing data flow
  • "One more fix" after 2+ failures

Human Signals You're Off Track

  • "Is that not happening?" β†’ You assumed without verifying
  • "Will it show us...?" β†’ You should have added evidence gathering
  • "Stop guessing" β†’ You're proposing fixes without understanding
  • "Ultrathink this" β†’ Question fundamentals
  • Frustrated "We're stuck?" β†’ Your approach isn't working

Response: Return to Phase 1.

Supporting Techniques

Reference files in references/:

  • root-cause-tracing.md - Trace bugs backward through call stack
  • defense-in-depth.md - Add validation at multiple layers after finding root cause
  • condition-based-waiting.md - Replace arbitrary timeouts with condition polling

Related skills:

  • test-driven-development - Creating failing test case (Phase 4)
  • verification-before-completion - Verify fix before claiming success

Gives 6 of the 12 instructions most debug triage skills give in ~1.0k tokens

Counted across 839 of the 1,149 authors here whose files we hold, read 2026-08-06

  • investigate root cause before proposing any fixhere, and in 102 of 839, across 65 files
  • read error messages completelyhere, and in 90 of 839, across 48 files
  • create a failing test case before fixinghere, and in 84 of 839, across 44 files
  • reproduce the issue consistentlyhere, and in 82 of 839, across 40 files
  • change one variable at a timein 82 of 839, across 42 files
  • check recent changeshere, and in 74 of 839, across 35 files
  • write the regression test before fixingin 74 of 839, across 36 files
  • fix the root cause not the symptomin 60 of 839, across 43 files
  • implement a single fix at a timein 59 of 839, across 20 files
  • trace data flow backward to the sourcein 50 of 839, across 20 files
  • remove all debug instrumentationin 49 of 839, across 13 files
  • form a single hypothesishere, and in 48 of 839, across 18 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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