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/why

Iterative Five Whys root cause analysis drilling from symptoms to fundamentals

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context-engineering-kit
1.3k134 skills23 agents1 command
Install
$ npx -y skills add NeoLabHQ/context-engineering-kit --skill why --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/why

Context preview

The summary Claude sees to decide when to auto-load this skill.

Iterative Five Whys root cause analysis drilling from symptoms to fundamentals

SKILL.md

why.SKILL.md
name: why
description: Iterative Five Whys root cause analysis drilling from symptoms to fundamentals
argument-hint: Optional issue or symptom description

Five Whys Analysis

Apply Five Whys root cause analysis to investigate issues by iteratively asking "why" to drill from symptoms to root causes.

Description

Iteratively ask "why" to move from surface symptoms to fundamental causes. Identifies systemic issues rather than quick fixes.

Usage

`/why [issue_description]`

Variables

  • ISSUE: Problem or symptom to analyze (default: prompt for input)
  • DEPTH: Number of "why" iterations (default: 5, adjust as needed)

Steps

1. State the problem clearly 2. Ask "Why did this happen?" and document the answer 3. For that answer, ask "Why?" again 4. Continue until reaching root cause (usually 5 iterations) 5. Validate by working backwards: root cause → symptom 6. Explore branches if multiple causes emerge 7. Propose solutions addressing root causes, not symptoms

Examples

Example 1: Production Bug

Problem: Users see 500 error on checkout
Why 1: Payment service throws exception
Why 2: Request timeout after 30 seconds
Why 3: Database query takes 45 seconds
Why 4: Missing index on transactions table
Why 5: Index creation wasn't in migration scripts
Root Cause: Migration review process doesn't check query performance

Solution: Add query performance checks to migration PR template

Example 2: CI/CD Pipeline Failures

Problem: E2E tests fail intermittently
Why 1: Race condition in async test setup
Why 2: Test doesn't wait for database seed completion
Why 3: Seed function doesn't return promise
Why 4: TypeScript didn't catch missing return type
Why 5: strict mode not enabled in test config
Root Cause: Inconsistent TypeScript config between src and tests

Solution: Unify TypeScript config, enable strict mode everywhere

Example 3: Multi-Branch Analysis

Problem: Feature deployment takes 2 hours

Branch A (Build):
Why 1: Docker build takes 90 minutes
Why 2: No layer caching
Why 3: Dependencies reinstalled every time
Why 4: Cache invalidated by timestamp in Dockerfile
Root Cause A: Dockerfile uses current timestamp for versioning

Branch B (Tests):
Why 1: Test suite takes 30 minutes
Why 2: Integration tests run sequentially
Why 3: Test runner config has maxWorkers: 1
Why 4: Previous developer disabled parallelism due to flaky tests
Root Cause B: Flaky tests masked by disabling parallelism

Solutions: 
A) Remove timestamp from Dockerfile, use git SHA
B) Fix flaky tests, re-enable parallel test execution

Notes

  • Don't stop at symptoms; keep digging for systemic issues
  • Multiple root causes may exist - explore different branches
  • Document each "why" for future reference
  • Consider both technical and process-related causes
  • The magic isn't in exactly 5 whys - stop when you reach the true root cause
  • Stop when you hit systemic/process issues, not just technical details
  • Multiple root causes are common—explore branches separately
  • If "human error" appears, keep digging: why was error possible?
  • Document every "why" for future reference
  • Root cause usually involves: missing validation, missing docs, unclear process, or missing automation
  • Test solutions: implement → verify symptom resolved → monitor for recurrence
Read more
Ships withcontext-engineering-kit

A hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint, focused on improving agent result quality and predictability.

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