Nw Leanux MethodologySAFE
AI agents that guide you from idea to working code, with you in control at every step.
Overview
AI agents that guide you from idea to working code, with you in control at every step.
1a864ec81cdeOBSERVED · 2026-10-14What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
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
```markdown
## 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", "[email protected]"
- Problem: Lacks real-world context, harder to validate
- Bad: "Given user123 logs in with password123"
- Good: "Given Maria Santos ([email protected]) 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
- ProblemTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-leanux-methodology.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-14 | 1a864ec81cde | SAFE | B | 89 | first audit |
Questions
What does the Nw Leanux Methodology skill do?
AI agents that guide you from idea to working code, with you in control at every step.
Is Nw Leanux Methodology safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Nw Leanux Methodology access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (1a864ec81cde), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.