Claude Skill

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

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Part of mvschwarz/openrig — 47 skills

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skills CLI npx skills add https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/process/systematic-debugging
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install mvschwarz-openrig@llmmart
Git git clone https://github.com/mvschwarz/openrig.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole mvschwarz/openrig collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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:

  1. 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
  2. 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
  3. Check Recent Changes

    • What changed that could cause this?
    • Git diff, recent commits
    • New dependencies, config changes
    • Environmental differences
  4. 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 ✗)

  5. 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:

  1. Find Working Examples

    • Locate similar working code in same codebase
    • What works that's similar to what's broken?
  2. Compare Against References

    • If implementing pattern, read reference implementation COMPLETELY
    • Don't skim - read every line
    • Understand the pattern fully before applying
  3. Identify Differences

    • What's different between working and broken?
    • List every difference, however small
    • Don't assume "that can't matter"
  4. Understand Dependencies

    • What other components does this need?
    • What settings, config, environment?
    • What assumptions does it make?

Phase 3: Hypothesis and Testing

Scientific method:

  1. Form Single Hypothesis

    • State clearly: "I think X is the root cause because Y"
    • Write it down
    • Be specific, not vague
  2. Test Minimally

    • Make the SMALLEST possible change to test hypothesis
    • One variable at a time
    • Don't fix multiple things at once
  3. Verify Before Continuing

    • Did it work? Yes → Phase 4
    • Didn't work? Form NEW hypothesis
    • DON'T add more fixes on top
  4. 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:

  1. 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
  2. Implement Single Fix

    • Address the root cause identified
    • ONE change at a time
    • No "while I'm here" improvements
    • No bundled refactoring
  3. Verify Fix

    • Test passes now?
    • No other tests broken?
    • Issue actually resolved?
  4. 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
  5. 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)

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.
"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.

Quick Reference

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

When Process Reveals "No Root Cause"

If systematic investigation reveals issue is truly environmental, timing-dependent, or external:

  1. You've completed the process
  2. Document what you investigated
  3. Implement appropriate handling (retry, timeout, error message)
  4. Add monitoring/logging for future investigation

But: 95% of "no root cause" cases are incomplete investigation.

Supporting Techniques

These techniques are part of systematic debugging and available in this directory:

  • root-cause-tracing.md - Trace bugs backward through call stack to find original trigger
  • 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:

  • superpowers:test-driven-development - For creating failing test case (Phase 4, Step 1)
  • superpowers:verification-before-completion - Verify fix worked before claiming success

Real-World Impact

From debugging sessions:

  • Systematic approach: 15-30 minutes to fix
  • Random fixes approach: 2-3 hours of thrashing
  • First-time fix rate: 95% vs 40%
  • New bugs introduced: Near zero vs common
Files (openrig)
  • condition-based-waiting-example.ts 4.9 KB
    // Complete implementation of condition-based waiting utilities
    // From: Lace test infrastructure improvements (2025-10-03)
    // Context: Fixed 15 flaky tests by replacing arbitrary timeouts
    
    import type { ThreadManager } from '~/threads/thread-manager';
    import type { LaceEvent, LaceEventType } from '~/threads/types';
    
    /**
     * Wait for a specific event type to appear in thread
     *
     * @param threadManager - The thread manager to query
     * @param threadId - Thread to check for events
     * @param eventType - Type of event to wait for
     * @param timeoutMs - Maximum time to wait (default 5000ms)
     * @returns Promise resolving to the first matching event
     *
     * Example:
     *   await waitForEvent(threadManager, agentThreadId, 'TOOL_RESULT');
     */
    export function waitForEvent(
      threadManager: ThreadManager,
      threadId: string,
      eventType: LaceEventType,
      timeoutMs = 5000
    ): Promise<LaceEvent> {
      return new Promise((resolve, reject) => {
        const startTime = Date.now();
    
        const check = () => {
          const events = threadManager.getEvents(threadId);
          const event = events.find((e) => e.type === eventType);
    
          if (event) {
            resolve(event);
          } else if (Date.now() - startTime > timeoutMs) {
            reject(new Error(`Timeout waiting for ${eventType} event after ${timeoutMs}ms`));
          } else {
            setTimeout(check, 10); // Poll every 10ms for efficiency
          }
        };
    
        check();
      });
    }
    
    /**
     * Wait for a specific number of events of a given type
     *
     * @param threadManager - The thread manager to query
     * @param threadId - Thread to check for events
     * @param eventType - Type of event to wait for
     * @param count - Number of events to wait for
     * @param timeoutMs - Maximum time to wait (default 5000ms)
     * @returns Promise resolving to all matching events once count is reached
     *
     * Example:
     *   // Wait for 2 AGENT_MESSAGE events (initial response + continuation)
     *   await waitForEventCount(threadManager, agentThreadId, 'AGENT_MESSAGE', 2);
     */
    export function waitForEventCount(
      threadManager: ThreadManager,
      threadId: string,
      eventType: LaceEventType,
      count: number,
      timeoutMs = 5000
    ): Promise<LaceEvent[]> {
      return new Promise((resolve, reject) => {
        const startTime = Date.now();
    
        const check = () => {
          const events = threadManager.getEvents(threadId);
          const matchingEvents = events.filter((e) => e.type === eventType);
    
          if (matchingEvents.length >= count) {
            resolve(matchingEvents);
          } else if (Date.now() - startTime > timeoutMs) {
            reject(
              new Error(
                `Timeout waiting for ${count} ${eventType} events after ${timeoutMs}ms (got ${matchingEvents.length})`
              )
            );
          } else {
            setTimeout(check, 10);
          }
        };
    
        check();
      });
    }
    
    /**
     * Wait for an event matching a custom predicate
     * Useful when you need to check event data, not just type
     *
     * @param threadManager - The thread manager to query
     * @param threadId - Thread to check for events
     * @param predicate - Function that returns true when event matches
     * @param description - Human-readable description for error messages
     * @param timeoutMs - Maximum time to wait (default 5000ms)
     * @returns Promise resolving to the first matching event
     *
     * Example:
     *   // Wait for TOOL_RESULT with specific ID
     *   await waitForEventMatch(
     *     threadManager,
     *     agentThreadId,
     *     (e) => e.type === 'TOOL_RESULT' && e.data.id === 'call_123',
     *     'TOOL_RESULT with id=call_123'
     *   );
     */
    export function waitForEventMatch(
      threadManager: ThreadManager,
      threadId: string,
      predicate: (event: LaceEvent) => boolean,
      description: string,
      timeoutMs = 5000
    ): Promise<LaceEvent> {
      return new Promise((resolve, reject) => {
        const startTime = Date.now();
    
        const check = () => {
          const events = threadManager.getEvents(threadId);
          const event = events.find(predicate);
    
          if (event) {
            resolve(event);
          } else if (Date.now() - startTime > timeoutMs) {
            reject(new Error(`Timeout waiting for ${description} after ${timeoutMs}ms`));
          } else {
            setTimeout(check, 10);
          }
        };
    
        check();
      });
    }
    
    // Usage example from actual debugging session:
    //
    // BEFORE (flaky):
    // ---------------
    // const messagePromise = agent.sendMessage('Execute tools');
    // await new Promise(r => setTimeout(r, 300)); // Hope tools start in 300ms
    // agent.abort();
    // await messagePromise;
    // await new Promise(r => setTimeout(r, 50));  // Hope results arrive in 50ms
    // expect(toolResults.length).toBe(2);         // Fails randomly
    //
    // AFTER (reliable):
    // ----------------
    // const messagePromise = agent.sendMessage('Execute tools');
    // await waitForEventCount(threadManager, threadId, 'TOOL_CALL', 2); // Wait for tools to start
    // agent.abort();
    // await messagePromise;
    // await waitForEventCount(threadManager, threadId, 'TOOL_RESULT', 2); // Wait for results
    // expect(toolResults.length).toBe(2); // Always succeeds
    //
    // Result: 60% pass rate → 100%, 40% faster execution
    
  • condition-based-waiting.md 3.4 KB
    # Condition-Based Waiting
    
    ## Overview
    
    Flaky tests often guess at timing with arbitrary delays. This creates race conditions where tests pass on fast machines but fail under load or in CI.
    
    **Core principle:** Wait for the actual condition you care about, not a guess about how long it takes.
    
    ## When to Use
    
    ```dot
    digraph when_to_use {
        "Test uses setTimeout/sleep?" [shape=diamond];
        "Testing timing behavior?" [shape=diamond];
        "Document WHY timeout needed" [shape=box];
        "Use condition-based waiting" [shape=box];
    
        "Test uses setTimeout/sleep?" -> "Testing timing behavior?" [label="yes"];
        "Testing timing behavior?" -> "Document WHY timeout needed" [label="yes"];
        "Testing timing behavior?" -> "Use condition-based waiting" [label="no"];
    }
    ```
    
    **Use when:**
    - Tests have arbitrary delays (`setTimeout`, `sleep`, `time.sleep()`)
    - Tests are flaky (pass sometimes, fail under load)
    - Tests timeout when run in parallel
    - Waiting for async operations to complete
    
    **Don't use when:**
    - Testing actual timing behavior (debounce, throttle intervals)
    - Always document WHY if using arbitrary timeout
    
    ## Core Pattern
    
    ```typescript
    // ❌ BEFORE: Guessing at timing
    await new Promise(r => setTimeout(r, 50));
    const result = getResult();
    expect(result).toBeDefined();
    
    // ✅ AFTER: Waiting for condition
    await waitFor(() => getResult() !== undefined);
    const result = getResult();
    expect(result).toBeDefined();
    ```
    
    ## Quick Patterns
    
    | Scenario | Pattern |
    |----------|---------|
    | Wait for event | `waitFor(() => events.find(e => e.type === 'DONE'))` |
    | Wait for state | `waitFor(() => machine.state === 'ready')` |
    | Wait for count | `waitFor(() => items.length >= 5)` |
    | Wait for file | `waitFor(() => fs.existsSync(path))` |
    | Complex condition | `waitFor(() => obj.ready && obj.value > 10)` |
    
    ## Implementation
    
    Generic polling function:
    ```typescript
    async function waitFor<T>(
      condition: () => T | undefined | null | false,
      description: string,
      timeoutMs = 5000
    ): Promise<T> {
      const startTime = Date.now();
    
      while (true) {
        const result = condition();
        if (result) return result;
    
        if (Date.now() - startTime > timeoutMs) {
          throw new Error(`Timeout waiting for ${description} after ${timeoutMs}ms`);
        }
    
        await new Promise(r => setTimeout(r, 10)); // Poll every 10ms
      }
    }
    ```
    
    See `condition-based-waiting-example.ts` in this directory for complete implementation with domain-specific helpers (`waitForEvent`, `waitForEventCount`, `waitForEventMatch`) from actual debugging session.
    
    ## Common Mistakes
    
    **❌ Polling too fast:** `setTimeout(check, 1)` - wastes CPU
    **✅ Fix:** Poll every 10ms
    
    **❌ No timeout:** Loop forever if condition never met
    **✅ Fix:** Always include timeout with clear error
    
    **❌ Stale data:** Cache state before loop
    **✅ Fix:** Call getter inside loop for fresh data
    
    ## When Arbitrary Timeout IS Correct
    
    ```typescript
    // Tool ticks every 100ms - need 2 ticks to verify partial output
    await waitForEvent(manager, 'TOOL_STARTED'); // First: wait for condition
    await new Promise(r => setTimeout(r, 200));   // Then: wait for timed behavior
    // 200ms = 2 ticks at 100ms intervals - documented and justified
    ```
    
    **Requirements:**
    1. First wait for triggering condition
    2. Based on known timing (not guessing)
    3. Comment explaining WHY
    
    ## Real-World Impact
    
    From debugging session (2025-10-03):
    - Fixed 15 flaky tests across 3 files
    - Pass rate: 60% → 100%
    - Execution time: 40% faster
    - No more race conditions
    
  • defense-in-depth.md 3.6 KB
    # Defense-in-Depth Validation
    
    ## Overview
    
    When you fix a bug caused by invalid data, adding validation at one place feels sufficient. But that single check can be bypassed by different code paths, refactoring, or mocks.
    
    **Core principle:** Validate at EVERY layer data passes through. Make the bug structurally impossible.
    
    ## Why Multiple Layers
    
    Single validation: "We fixed the bug"
    Multiple layers: "We made the bug impossible"
    
    Different layers catch different cases:
    - Entry validation catches most bugs
    - Business logic catches edge cases
    - Environment guards prevent context-specific dangers
    - Debug logging helps when other layers fail
    
    ## The Four Layers
    
    ### Layer 1: Entry Point Validation
    **Purpose:** Reject obviously invalid input at API boundary
    
    ```typescript
    function createProject(name: string, workingDirectory: string) {
      if (!workingDirectory || workingDirectory.trim() === '') {
        throw new Error('workingDirectory cannot be empty');
      }
      if (!existsSync(workingDirectory)) {
        throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
      }
      if (!statSync(workingDirectory).isDirectory()) {
        throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
      }
      // ... proceed
    }
    ```
    
    ### Layer 2: Business Logic Validation
    **Purpose:** Ensure data makes sense for this operation
    
    ```typescript
    function initializeWorkspace(projectDir: string, sessionId: string) {
      if (!projectDir) {
        throw new Error('projectDir required for workspace initialization');
      }
      // ... proceed
    }
    ```
    
    ### Layer 3: Environment Guards
    **Purpose:** Prevent dangerous operations in specific contexts
    
    ```typescript
    async function gitInit(directory: string) {
      // In tests, refuse git init outside temp directories
      if (process.env.NODE_ENV === 'test') {
        const normalized = normalize(resolve(directory));
        const tmpDir = normalize(resolve(tmpdir()));
    
        if (!normalized.startsWith(tmpDir)) {
          throw new Error(
            `Refusing git init outside temp dir during tests: ${directory}`
          );
        }
      }
      // ... proceed
    }
    ```
    
    ### Layer 4: Debug Instrumentation
    **Purpose:** Capture context for forensics
    
    ```typescript
    async function gitInit(directory: string) {
      const stack = new Error().stack;
      logger.debug('About to git init', {
        directory,
        cwd: process.cwd(),
        stack,
      });
      // ... proceed
    }
    ```
    
    ## Applying the Pattern
    
    When you find a bug:
    
    1. **Trace the data flow** - Where does bad value originate? Where used?
    2. **Map all checkpoints** - List every point data passes through
    3. **Add validation at each layer** - Entry, business, environment, debug
    4. **Test each layer** - Try to bypass layer 1, verify layer 2 catches it
    
    ## Example from Session
    
    Bug: Empty `projectDir` caused `git init` in source code
    
    **Data flow:**
    1. Test setup → empty string
    2. `Project.create(name, '')`
    3. `WorkspaceManager.createWorkspace('')`
    4. `git init` runs in `process.cwd()`
    
    **Four layers added:**
    - Layer 1: `Project.create()` validates not empty/exists/writable
    - Layer 2: `WorkspaceManager` validates projectDir not empty
    - Layer 3: `WorktreeManager` refuses git init outside tmpdir in tests
    - Layer 4: Stack trace logging before git init
    
    **Result:** All 1847 tests passed, bug impossible to reproduce
    
    ## Key Insight
    
    All four layers were necessary. During testing, each layer caught bugs the others missed:
    - Different code paths bypassed entry validation
    - Mocks bypassed business logic checks
    - Edge cases on different platforms needed environment guards
    - Debug logging identified structural misuse
    
    **Don't stop at one validation point.** Add checks at every layer.
    
  • find-polluter.sh 2 KB
    #!/usr/bin/env bash
    # Bisection script to find which test creates unwanted files/state
    # Usage: ./find-polluter.sh <file_or_dir_to_check> <test_pattern>
    # Example: ./find-polluter.sh '.git' 'src/**/*.test.ts'
    
    # Exit 0: every selected test succeeded without pollution; 1: polluter found;
    # 2: no result (invalid input, selection failure, or incomplete test runs).
    set -eo pipefail
    
    if [ $# -ne 2 ]; then
      echo "Usage: $0 <file_to_check> <test_pattern>"
      echo "Example: $0 '.git' 'src/**/*.test.ts'"
      exit 2
    fi
    
    POLLUTION_CHECK="$1"
    TEST_PATTERN="$2"
    
    echo "🔍 Searching for test that creates: $POLLUTION_CHECK"
    echo "Test pattern: $TEST_PATTERN"
    echo ""
    
    # Get list of test files
    if ! TEST_FILES=$(find . -type f -path "./${TEST_PATTERN#./}" | sort); then
      echo "Test selection failed; no tests ran."
      exit 2
    fi
    if [ -z "$TEST_FILES" ]; then
      echo "No test files matched; no tests ran."
      exit 2
    fi
    TOTAL=$(printf '%s\n' "$TEST_FILES" | wc -l | tr -d ' ')
    
    echo "Found $TOTAL test files"
    echo ""
    
    COUNT=0
    FAILED=0
    if [ -e "$POLLUTION_CHECK" ]; then
      echo "Pollution already exists before testing; no tests ran."
      exit 2
    fi
    while IFS= read -r TEST_FILE; do
      COUNT=$((COUNT + 1))
    
      echo "[$COUNT/$TOTAL] Testing: $TEST_FILE"
    
      # Run the test
      if ! npm test "$TEST_FILE" > /dev/null 2>&1; then
        FAILED=$((FAILED + 1))
        echo "Test run failed: $TEST_FILE"
      fi
    
      # Check if pollution appeared
      if [ -e "$POLLUTION_CHECK" ]; then
        echo ""
        echo "🎯 FOUND POLLUTER!"
        echo "   Test: $TEST_FILE"
        echo "   Created: $POLLUTION_CHECK"
        echo ""
        echo "Pollution details:"
        ls -la "$POLLUTION_CHECK"
        echo ""
        echo "To investigate:"
        echo "  npm test $TEST_FILE    # Run just this test"
        echo "  cat $TEST_FILE         # Review test code"
        exit 1
      fi
    done <<< "$TEST_FILES"
    
    echo ""
    if [ "$FAILED" -gt 0 ]; then
      echo "Incomplete: $FAILED test runs failed; no polluter observed."
      exit 2
    fi
    echo "✅ No polluter found - $COUNT test runs succeeded without pollution."
    exit 0
    
  • root-cause-tracing.md 5.2 KB
    # Root Cause Tracing
    
    ## Overview
    
    Bugs often manifest deep in the call stack (git init in wrong directory, file created in wrong location, database opened with wrong path). Your instinct is to fix where the error appears, but that's treating a symptom.
    
    **Core principle:** Trace backward through the call chain until you find the original trigger, then fix at the source.
    
    ## When to Use
    
    ```dot
    digraph when_to_use {
        "Bug appears deep in stack?" [shape=diamond];
        "Can trace backwards?" [shape=diamond];
        "Fix at symptom point" [shape=box];
        "Trace to original trigger" [shape=box];
        "BETTER: Also add defense-in-depth" [shape=box];
    
        "Bug appears deep in stack?" -> "Can trace backwards?" [label="yes"];
        "Can trace backwards?" -> "Trace to original trigger" [label="yes"];
        "Can trace backwards?" -> "Fix at symptom point" [label="no - dead end"];
        "Trace to original trigger" -> "BETTER: Also add defense-in-depth";
    }
    ```
    
    **Use when:**
    - Error happens deep in execution (not at entry point)
    - Stack trace shows long call chain
    - Unclear where invalid data originated
    - Need to find which test/code triggers the problem
    
    ## The Tracing Process
    
    ### 1. Observe the Symptom
    ```
    Error: git init failed in /Users/jesse/project/packages/core
    ```
    
    ### 2. Find Immediate Cause
    **What code directly causes this?**
    ```typescript
    await execFileAsync('git', ['init'], { cwd: projectDir });
    ```
    
    ### 3. Ask: What Called This?
    ```typescript
    WorktreeManager.createSessionWorktree(projectDir, sessionId)
      → called by Session.initializeWorkspace()
      → called by Session.create()
      → called by test at Project.create()
    ```
    
    ### 4. Keep Tracing Up
    **What value was passed?**
    - `projectDir = ''` (empty string!)
    - Empty string as `cwd` resolves to `process.cwd()`
    - That's the source code directory!
    
    ### 5. Find Original Trigger
    **Where did empty string come from?**
    ```typescript
    const context = setupCoreTest(); // Returns { tempDir: '' }
    Project.create('name', context.tempDir); // Accessed before beforeEach!
    ```
    
    ## Adding Stack Traces
    
    When you can't trace manually, add instrumentation:
    
    ```typescript
    // Before the problematic 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 });
    }
    ```
    
    **Critical:** Use `console.error()` in tests (not logger - may not show)
    
    **Run and capture:**
    ```bash
    npm test 2>&1 | grep 'DEBUG git init'
    ```
    
    **Analyze stack traces:**
    - Look for test file names
    - Find the line number triggering the call
    - Identify the pattern (same test? same parameter?)
    
    ## Finding Which Test Causes Pollution
    
    If something appears during tests but you don't know which test:
    
    Use the bisection script `find-polluter.sh` in this directory:
    
    ```bash
    ./find-polluter.sh '.git' 'src/**/*.test.ts'
    ```
    
    Runs tests one-by-one, stops at first polluter. See script for usage.
    
    ## Real Example: Empty projectDir
    
    **Symptom:** `.git` created in `packages/core/` (source code)
    
    **Trace chain:**
    1. `git init` runs in `process.cwd()` ← empty cwd parameter
    2. WorktreeManager called with empty projectDir
    3. Session.create() passed empty string
    4. Test accessed `context.tempDir` before beforeEach
    5. setupCoreTest() returns `{ tempDir: '' }` initially
    
    **Root cause:** Top-level variable initialization accessing empty value
    
    **Fix:** Made tempDir a getter that throws if accessed before beforeEach
    
    **Also added defense-in-depth:**
    - Layer 1: Project.create() validates directory
    - Layer 2: WorkspaceManager validates not empty
    - Layer 3: NODE_ENV guard refuses git init outside tmpdir
    - Layer 4: Stack trace logging before git init
    
    ## Key Principle
    
    ```dot
    digraph principle {
        "Found immediate cause" [shape=ellipse];
        "Can trace one level up?" [shape=diamond];
        "Trace backwards" [shape=box];
        "Is this the source?" [shape=diamond];
        "Fix at source" [shape=box];
        "Add validation at each layer" [shape=box];
        "Bug impossible" [shape=doublecircle];
        "NEVER fix just the symptom" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
    
        "Found immediate cause" -> "Can trace one level up?";
        "Can trace one level up?" -> "Trace backwards" [label="yes"];
        "Can trace one level up?" -> "NEVER fix just the symptom" [label="no"];
        "Trace backwards" -> "Is this the source?";
        "Is this the source?" -> "Trace backwards" [label="no - keeps going"];
        "Is this the source?" -> "Fix at source" [label="yes"];
        "Fix at source" -> "Add validation at each layer";
        "Add validation at each layer" -> "Bug impossible";
    }
    ```
    
    **NEVER fix just where the error appears.** Trace back to find the original trigger.
    
    ## Stack Trace Tips
    
    **In tests:** Use `console.error()` not logger - logger may be suppressed
    **Before operation:** Log before the dangerous operation, not after it fails
    **Include context:** Directory, cwd, environment variables, timestamps
    **Capture stack:** `new Error().stack` shows complete call chain
    
    ## Real-World Impact
    
    From debugging session (2025-10-03):
    - Found root cause through 5-level trace
    - Fixed at source (getter validation)
    - Added 4 layers of defense
    - 1847 tests passed, zero pollution
    
  • SKILL.md 9.9 KB
    ---
    name: systematic-debugging
    description: Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
    metadata:
      openrig:
        vendored_from: "Obra Superpowers (https://github.com/obra/superpowers)"
        vendoring_pattern: vendored-as-is
        last_upstream_check: "2026-05-13 (diff against plugin source pulled 2026-05-11 = identical)"
    ---
    
    # 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:**
    
    1. **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
    
    2. **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
    
    3. **Check Recent Changes**
       - What changed that could cause this?
       - Git diff, recent commits
       - New dependencies, config changes
       - Environmental differences
    
    4. **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):**
       ```bash
       # 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 ✗)
    
    5. **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:**
    
    1. **Find Working Examples**
       - Locate similar working code in same codebase
       - What works that's similar to what's broken?
    
    2. **Compare Against References**
       - If implementing pattern, read reference implementation COMPLETELY
       - Don't skim - read every line
       - Understand the pattern fully before applying
    
    3. **Identify Differences**
       - What's different between working and broken?
       - List every difference, however small
       - Don't assume "that can't matter"
    
    4. **Understand Dependencies**
       - What other components does this need?
       - What settings, config, environment?
       - What assumptions does it make?
    
    ### Phase 3: Hypothesis and Testing
    
    **Scientific method:**
    
    1. **Form Single Hypothesis**
       - State clearly: "I think X is the root cause because Y"
       - Write it down
       - Be specific, not vague
    
    2. **Test Minimally**
       - Make the SMALLEST possible change to test hypothesis
       - One variable at a time
       - Don't fix multiple things at once
    
    3. **Verify Before Continuing**
       - Did it work? Yes → Phase 4
       - Didn't work? Form NEW hypothesis
       - DON'T add more fixes on top
    
    4. **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:**
    
    1. **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
    
    2. **Implement Single Fix**
       - Address the root cause identified
       - ONE change at a time
       - No "while I'm here" improvements
       - No bundled refactoring
    
    3. **Verify Fix**
       - Test passes now?
       - No other tests broken?
       - Issue actually resolved?
    
    4. **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
    
    5. **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)
    
    ## 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. |
    | "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. |
    
    ## Quick Reference
    
    | 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 |
    
    ## When Process Reveals "No Root Cause"
    
    If systematic investigation reveals issue is truly environmental, timing-dependent, or external:
    
    1. You've completed the process
    2. Document what you investigated
    3. Implement appropriate handling (retry, timeout, error message)
    4. Add monitoring/logging for future investigation
    
    **But:** 95% of "no root cause" cases are incomplete investigation.
    
    ## Supporting Techniques
    
    These techniques are part of systematic debugging and available in this directory:
    
    - **`root-cause-tracing.md`** - Trace bugs backward through call stack to find original trigger
    - **`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:**
    - **superpowers:test-driven-development** - For creating failing test case (Phase 4, Step 1)
    - **superpowers:verification-before-completion** - Verify fix worked before claiming success
    
    ## Real-World Impact
    
    From debugging sessions:
    - Systematic approach: 15-30 minutes to fix
    - Random fixes approach: 2-3 hours of thrashing
    - First-time fix rate: 95% vs 40%
    - New bugs introduced: Near zero vs common
    

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