nw-diverge

nw-diverge is a skill for Claude Code from nWave-ai/nWave. It costs 45 tokens per session (1,966 once invoked), scanned A, original, MIT.

A structured design-exploration workflow that turns a validated problem into three to five different solution directions before the team chooses one. It combines user-job analysis, competitor research, brainstorming, and evaluation.

In plain words
What is it for?
It helps explore new products, existing-feature changes, or redesigns by researching alternatives, generating design directions, scoring them, and recommending one.
Why use it?
It reduces the risk of committing too early to the first idea and gives the team concrete alternatives to compare.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: reads .claude/ paths; mentions subagents.

Good fit It helps explore new products, existing-feature changes, or redesigns by researching alternatives, generating design directions, scoring them, and recommending one.

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Install with agentmods
npx agentmods add skills/nwave-ai/nwave/nw-diverge
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-diverge
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-diverge

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nw-diverge

Your own site · 80×15
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Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,966 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 $0.00045 $0.01966
Opus 5 $0.00023 $0.00983
Sonnet 5 $0.00009 $0.00393
Haiku 4.5 $0.00005 $0.00197

Measured 6d ago against content hash 70b9da265d91, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

nw-diverge 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-diverge/SKILL.md · 164 lines

How it starts

The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NW-DIVERGE: Structured Divergent Thinking Before Convergence

Wave: DIVERGE (between DISCOVER and DISCUSS, optional) | Agent: Flux (nw-diverger) | Command: /nw-diverge

Overview

Execute DIVERGE wave through Flux's 4-phase workflow: JTBD analysis|competitive research|structured brainstorming|taste-filtered evaluation. Transforms a validated problem into 3-5 concrete, taste-scored design directions so DISCUSS can converge on one with confidence.

DIVERGE is optional. Brownfield features with a clear direction may skip it (see skip checklist in design spec). New products and pivot decisions benefit most from structured divergence.

Interactive Decision Points

Decision 1: Work Type

Question: What type of work is this? Options:

  1. New product -- no prior solution exists, full divergence needed
  2. Brownfield feature -- existing product, exploring approach alternatives
  3. Pivot / redesign -- existing feature being reconsidered from scratch
  4. Other -- user provides custom context

Decision 2: Research Depth

Question: How deep should competitive research go? Options:

  1. Lightweight -- 3 competitors, known market
  2. Comprehensive -- 5+ competitors including non-obvious alternatives
  3. Deep-dive -- cross-category research, adjacent markets, academic references

Prior Wave Consultation

Before beginning DIVERGE work, read SSOT and prior wave artifacts:

  1. SSOT (if docs/product/ exists):
    • docs/product/jobs.yaml -- validated jobs and opportunity scores
    • docs/product/vision.md -- product vision and strategic context
  2. Project context: docs/project-brief.md | docs/stakeholders.yaml (if available)
  3. DISCOVER artifacts: Read docs/feature/{feature-id}/discover/ (if present)
    • wave-decisions.md -- validated assumptions and key decisions
    • problem-validation.md -- customer evidence grounding the problem

Migration gate: If docs/product/ does not exist but docs/feature/ has existing features, STOP. Guide the user to docs/guides/migrating-to-ssot-model/README.md and complete the migration first. If greenfield, DIVERGE will bootstrap docs/product/jobs.yaml with the validated job.

Read the full file on GitHub · 164 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 · 164 lines · 45 tokens per session scan A 70b9da265d91

Subscribe to this mod's changes

nw-diverge is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 3d ago), licensed MIT. It adds 45 tokens to every session and 1,966 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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