kaizen:root-cause-tracing

neolabhq/context-engineering-kit · updated Apr 8, 2026

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$npx skills add https://github.com/neolabhq/context-engineering-kit --skill kaizen:root-cause-tracing
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summary

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.

skill.md

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

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?

await execFileAsync('git', ['init'], { cwd: projectDir });

3. Ask: What Called This?

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?

const context = setupCoreTest(); // Returns { tempDir: '' }
Project.create('name', context.tempDir); // Accessed before beforeEach!

Adding Stack Traces

When you can't trace manually, add instrumentation:

// 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:

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

./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

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
how to use kaizen:root-cause-tracing

How to use kaizen:root-cause-tracing on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add kaizen:root-cause-tracing
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/neolabhq/context-engineering-kit --skill kaizen:root-cause-tracing

The skills CLI fetches kaizen:root-cause-tracing from GitHub repository neolabhq/context-engineering-kit and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/kaizen:root-cause-tracing

Reload or restart Cursor to activate kaizen:root-cause-tracing. Access the skill through slash commands (e.g., /kaizen:root-cause-tracing) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.629 reviews
  • Anika Zhang· Dec 28, 2024

    Keeps context tight: kaizen:root-cause-tracing is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Anika Harris· Nov 19, 2024

    Registry listing for kaizen:root-cause-tracing matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Michael Flores· Nov 11, 2024

    Useful defaults in kaizen:root-cause-tracing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Anika Singh· Oct 10, 2024

    kaizen:root-cause-tracing reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Michael Lopez· Oct 2, 2024

    I recommend kaizen:root-cause-tracing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kwame Diallo· Sep 21, 2024

    Solid pick for teams standardizing on skills: kaizen:root-cause-tracing is focused, and the summary matches what you get after install.

  • Oshnikdeep· Sep 9, 2024

    kaizen:root-cause-tracing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Chinedu Garcia· Sep 1, 2024

    kaizen:root-cause-tracing has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Aug 28, 2024

    Keeps context tight: kaizen:root-cause-tracing is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chinedu Gill· Aug 20, 2024

    Solid pick for teams standardizing on skills: kaizen:root-cause-tracing is focused, and the summary matches what you get after install.

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