nw-leanux-methodology

nw-leanux-methodology is a skill for Claude Code from nWave-ai/nWave. It costs 37 tokens per session (1,979 once invoked), scanned A, original, MIT.

A Lean UX guide for managing a software backlog as a set of tested hypotheses rather than a simple to-do list. It defines story formats, readiness and completion rules, sizing guidance, and ways to split large stories.

In plain words
What is it for?
Use it to write and size user stories, decide when work is ready, define done, detect oversized items, and split them into independently useful pieces.
Why use it?
Backlog items that are too vague or too large are hard to estimate, test, and finish. Clear states and smaller outcome-focused stories make work easier to prepare and track.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit Use it to write and size user stories, decide when work is ready, define done, detect oversized items, and split them into independently useful pieces.

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Install with agentmods
npx agentmods add skills/nwave-ai/nwave/nw-leanux-methodology
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add nWave-ai/nWave --skill nw-leanux-methodology
Clone the repo
git clone --depth 1 https://github.com/nWave-ai/nWave

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nw-leanux-methodology

README.md
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Your own site
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Your own site · 80×15
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Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,979 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.01979
Opus 5 $0.00018 $0.00989
Sonnet 5 $0.00007 $0.00396
Haiku 4.5 $0.00004 $0.00198

Measured 6d ago against content hash 1ad4f2bb74a2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

nw-leanux-methodology scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

nWave/skills/nw-leanux-methodology/SKILL.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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"

Read the full file on GitHub · 210 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 210 lines · 37 tokens per session scan A 1ad4f2bb74a2

Subscribe to this mod's changes

nw-leanux-methodology is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 3d ago), licensed MIT. It adds 37 tokens to every session and 1,979 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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