Nw User Story MappingSAFE
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-user-story-mapping
description: User story mapping for backlog management and outcome-based prioritization. Load during Phase 2.5 (User Story Mapping) to produce story-map.md and prioritization.md.
user-invocable: false
disable-model-invocation: true
---
# User Story Mapping
Create story maps that organize user stories spatially by activity and priority, then slice releases by outcome impact. Reference: Jeff Patton, "User Story Mapping" (2014). Integrates outcome-based prioritization from Gothelf/Seiden and riskiest-assumption-first from Maurya.
## Story Map Anatomy
| Element | Position | Purpose |
|---------|----------|---------|
| **Backbone** | Top row, left-to-right | User activities in chronological order -- the spine of the journey |
| **Ribs** | Columns under each activity | User tasks broken down vertically by detail and priority |
| **Walking Skeleton** | Horizontal line across all activities | Thinnest possible end-to-end working flow. Not an MVP -- it is the minimum slice that connects ALL activities |
| **Release Slices** | Horizontal bands below skeleton | Coherent groups of stories, each adding incremental value tied to a specific outcome |
Visual structure:
```
Activity A Activity B Activity C Activity D
----------- ----------- ----------- -----------
Task A.1 Task B.1 Task C.1 Task D.1 <- Walking Skeleton
........... ........... ........... ........... <- skeleton line
Task A.2 Task B.2 Task C.2 Task D.2 <- Release 1
Task A.3 Task B.3 <- Release 1
Task B.4 Task C.3 Task D.3 <- Release 2
```
## Building the Map
### Step 1: Frame the journey
Identify the user persona and their end-to-end goal. One map per persona-goal pair.
### Step 2: Map the backbone
Write the big activities left-to-right in chronological order. These are verb phrases: "Search products", "Compare options", "Complete purchase". Aim for 4-8 activities.
### Step 3: Fill the ribs
Under each activity, list the tasks that support it. Write as short action phrases (user behaviors). Place more detail and less critical tasks lower.
### Step 4: Prioritize vertically
Reorder tasks within each column: most critical at top, nice-to-have at bottom. Ask: "Which task is essential for this activity to work at all?"
### Step 5: Draw the walking skeleton
Draw a horizontal line that captures exactly one task from each activity -- the thinnest slice that delivers end-to-end flow. Every activity must be represented. If an activity has no task above the line, the skeleton is incomplete.
### Step 6: Slice into releases by outcome
Group remaining tasks into horizontal bands. Each band targets a specific outcome KPI. Name each release by the outcome it achieves, not the features it contains.
## Outcome-Based Prioritization
Prioritize releases by outcome impact, not feature completeness. Each release slice targets a specific measurable behavior change.
### Prioritization Formula
**Value** (outcome impact) x **Urgency** (time-sensitivity) / **Effort** (complexity) = **Priority Score**
Where (1-5 scale):
- **Value** (1-5) = outcome impact. 5 = moves north-star KPI significantly. 1 = marginal improvement. In Phase 2.5, estimate from discovery insights; refine in Phase 4 after outcome-kpis.md exists.
- **Urgency** (1-5) = time-sensitivity. 5 = time-critical or derisks fatal assumption. 1 = evergreen, no deadline.
- **Effort** (1-5) = complexity. 5 = many tasks, cross-cutting, unknowns. 1 = single task, well-understood.
- **Tie-breaking**: Walking Skeleton > Riskiest Assumption > Highest Value.
### Riskiest Assumption First
From Running Lean (Maurya): validate what could kill the product before optimizing what improves it.
| Priority | What to validate | Why |
|----------|-----------------|-----|
| 1st | Walking skeleton | Does the end-to-end flow work at all? |
| 2nd | Release targeting riskiest assumption | Could this assumption kill the product? |
| 3rd | Release targeting highest-value outcome | Which behavior change drives the most impact? |
| 4th+ | Remaining releases by Value x Urgency / Effort | Incremental value delivery |
### Connecting to Outcomes
Each release slice maps to the logic model chain (Gothelf/Seiden):
```
Release Slice -> Output (features built)
-> Outcome (behavior change: [Who] [Does what] [By how much])
-> Impact (business KPI moved)
```
## Story Map Template (story-map.md)
```markdown
# Story Map: {feature-name}
## User: {persona}
## Goal: {what they're trying to accomplish}
## Backbone
| Activity 1 | Activity 2 | Activity 3 | Activity N |
|------------|------------|------------|------------|
| Task 1.1 | Task 2.1 | Task 3.1 | Task N.1 |
| Task 1.2 | Task 2.2 | Task 3.2 | |
| | Task 2.3 | | |
---
### Walking Skeleton
{List the minimum tasks from each activity that form the thinnest end-to-end slice}
### Release 1: {outcome target}
{Tasks included, outcome KPI targeted, rationale}
### Release 2: {outcome target}
{Tasks included, outcome KPI targeted, rationale}
```
## Prioritization Template (prioritization.md)
```markdown
# Prioritization: {feature-name}
## Release Priority
| Priority | Release | Target Outcome | KPI | Rationale |
|----------|---------|---------------|-----|-----------|
| 1 | Walking Skeleton | End-to-end flow works | {KPI} | Validates core assumption |
| 2 | {name} | {outcome} | {KPI} | {why this order} |
## Backlog Suggestions
| Story | Release | Priority | Outcome Link | Dependencies |
|-------|---------|----------|-------------|--------------|
| US-01 | WS | P1 | {KPI-1} | None |
| US-02 | R1 | P2 | {KPI-2} | US-01 |
> **Note**: In Phase 2.5, stories are task-level placeholders (e.g., "Search by category").
> Story IDs (US-01) are assigned in Phase 4 (Requirements). Revisit this table after Phase 4.
```
## Anti-Patterns
| AntiTrust 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-user-story-mapping.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 User Story Mapping skill do?
AI agents that guide you from idea to working code, with you in control at every step.
Is Nw User Story Mapping 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 User Story Mapping 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.