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LeanUX backlog management methodology - user story template, story sizing, story states, task types, Definition of Ready/Done, anti-pattern detection and remediation

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LeanUX backlog management methodology - user story template, story sizing, story states, task types, Definition of Ready/Done, anti-pattern detection and remediation

SKILL.md

nw-leanux-methodology.SKILL.md
name: nw-leanux-methodology
description: LeanUX backlog management methodology - user story template, story sizing, story states, task types, Definition of Ready/Done, anti-pattern detection and remediation
user-invocable: false
disable-model-invocation: true

LeanUX Backlog Management Methodology

"A backlog is not a todo list. It's a collection of validated hypotheses waiting to become working software."

Story States

| State | Meaning | Entry Criteria | |-------|---------|----------------| | Draft | Idea captured, not validated | Has problem statement | | Ready | Validated, has UAT, ready to build | All DoR items complete | | In Progress | Actively being built | UAT test written (RED) | | In Review | Code complete, awaiting review | All tests green | | Done | Merged, deployed, validated | UAT passes in production | | Blocked | Cannot proceed | Blocker documented |

Story Sizing Criteria

Right-Sized

Completable in 1-3 days | 3-7 UAT scenarios | Delivers demonstrable value | Explainable in 2 minutes

Oversized Indicators

>7 UAT scenarios | >3 days effort | Multiple distinct user outcomes | Cannot demonstrate in single session

Splitting Strategy

Split by user outcome, not technical layer. Each resulting story delivers independently demonstrable value.

Example: "User Management" (20 scenarios) splits into:

  • "Quick Login" (5 scenarios) -- returning customer on trusted device
  • "New Registration" (4 scenarios) -- first-time customer sign-up
  • "Password Recovery" (3 scenarios) -- customer who forgot credentials
  • "Profile Settings" (4 scenarios) -- customer updating preferences

Definition of Ready (DoR) - Hard Gate

Stories pass ALL 8 items before proceeding to DESIGN wave.

Checklist with Pass/Fail Examples

**1. Problem statement clear and in domain language**

  • Pass: "Maria wastes 30 seconds typing credentials on every visit"
  • Fail: "Users need authentication"

**2. User/persona identified with specific characteristics**

  • Pass: "Returning customer (2+ orders) on trusted personal device"
  • Fail: "User" or "Customer"

**3. At least 3 domain examples with real data**

  • Pass: "Maria on her MacBook, last login 5 days ago, goes directly to dashboard"
  • Fail: "User logs in successfully"

**4. UAT scenarios in Given/When/Then (3-7 scenarios)**

  • Pass: "Given Maria authenticated 5 days ago on 'MacBook-Home'..."
  • Fail: "Test login functionality"

**5. Acceptance criteria derived from UAT**

  • Pass: "Sessions older than 30 days require re-authentication"
  • Fail: "System should work correctly"

**6. Story right-sized (1-3 days, 3-7 scenarios)**

  • Pass: "2 days effort, 5 scenarios, single demo-able feature"
  • Fail: "Epic with 20 scenarios"

**7. Technical notes identify constraints**

  • Pass: "Requires JWT token storage, GDPR cookie consent"
  • Fail: "No technical considerations"

**8. Dependencies resolved or tracked**

  • Pass: "Depends on US-041 (completed) and Auth service API (available)"
  • Fail: "Unspecified external dependencies"

Validation Output Format

## Definition of Ready Validation

### Story: {story-id}

| DoR Item | Status | Evidence/Issue |
|----------|--------|----------------|
| Problem statement clear | PASS/FAIL | {evidence or issue} |
| User/persona identified | PASS/FAIL | {evidence or issue} |
| 3+ domain examples | PASS/FAIL | {evidence or issue} |
| UAT scenarios (3-7) | PASS/FAIL | {evidence or issue} |
| AC derived from UAT | PASS/FAIL | {evidence or issue} |
| Right-sized | PASS/FAIL | {evidence or issue} |
| Technical notes | PASS/FAIL | {evidence or issue} |
| Dependencies tracked | PASS/FAIL | {evidence or issue} |

### DoR Status: PASSED / BLOCKED

Failure Recovery

When DoR fails: 1. Display specific failures with remediation guidance 2. Do not proceed to peer review or handoff 3. Return to user with action items 4. Re-validate after fixes applied

Definition of Done (DoD) - Completion Criteria

DoD validation owned by acceptance-designer during DISTILL->DELIVER transition. Product-owner defines checklist, acceptance-designer enforces.

Checklist:

  • All UAT scenarios pass (green) | All supporting tests pass (unit, integration, component)
  • Code refactored, no obvious debt | Code reviewed and approved
  • Merged to main branch | Deployed to staging/production
  • Story can be demoed to user

Anti-Pattern Detection and Remediation

Implement-X

  • Signal: Task starts with "Implement X" or "Add X"
  • Problem: No user context, technical focus, vague completion
  • Bad: "Implement user authentication"
  • Good: "Returning Customer Quick Login -- Maria wastes 30 seconds..."
  • Fix: Start with user pain point, rewrite as problem statement

Generic Data

  • Signal: Examples use "user123", "test@test.com"
  • Problem: Lacks real-world context, harder to validate
  • Bad: "Given user123 logs in with password123"
  • Good: "Given Maria Santos (maria.santos@email.com) on her MacBook"
  • Fix: Replace all generic data with real names and realistic values

Technical Acceptance Criteria

  • Signal: AC describes implementation ("Use JWT tokens")
  • Problem: Prescribes solution, not testable outcome
  • Bad: "Use JWT tokens for session management"
  • Good: "Session persists for 30 days on trusted device"
  • Fix: Focus on observable user outcome, move tech choices to DESIGN

Oversized Stories

  • Signal: >7 scenarios or >3 days effort
  • Problem: Too large to track, deliver, or demo meaningfully
  • Bad: "Complete user management (20 scenarios)"
  • Good: "Quick Login (5 scenarios), Password Reset (4 scenarios)"
  • Fix: Split into focused stories by user outcome

No Examples

  • Signal: Abstract requirements without concrete examples
  • Problem: Ambiguous, untestable, different interpretations
  • Bad: "Users should be able to manage their settings"
  • Good: "Maria changes notification frequency from daily to weekly"
  • Fix: Add 3+ concrete narratives with real data

Tests After Code

  • Signal: Tests written after implementation
  • Problem
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