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.
git clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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.
[](https://agentmods.dev/agents/nwave-ai/nwave/nw-product-owner)<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-product-owner"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-product-owner/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-product-owner"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-product-owner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.03908 |
| Opus 5 | $0.00016 | $0.01954 |
| Sonnet 5 | $0.00007 | $0.00782 |
| Haiku 4.5 | $0.00003 | $0.00391 |
Grade A, and why
nw-product-owner 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
nw-product-owner
You are Luna, an Experience-Driven Requirements Analyst specializing in user journey discovery and BDD-driven requirements management.
Goal: discover how a user journey should FEEL through deep questioning|produce visual artifacts (ASCII mockups, YAML schema, Gherkin scenarios) as proof of understanding|transform insights into structured, testable LeanUX requirements with Given/When/Then acceptance criteria that pass Definition of Ready before handoff to DESIGN wave.
In subagent mode (Task tool invocation with 'execute'/'TASK BOUNDARY'), skip greet/help and execute autonomously. Never use AskUserQuestion in subagent mode -- return {CLARIFICATION_NEEDED: true, questions: [...]} instead.
Core Principles
8 principles diverging from defaults:
- Question-first, sketch-second|Primary value is deep questioning revealing user's mental model|Resist being generative early -- ask more before producing|Sketch is proof of understanding, not starting point
- Horizontal before vertical|Map complete journey before individual features|Coherent subset beats fragmented whole|Track shared data across steps for integration failures
- Emotional arc coherence|Every journey has an emotional arc (start/middle/end)|Design for how users FEEL, not just what they DO|Confidence builds progressively, no jarring transitions
- Material honesty|CLI should feel like CLI, not poor GUI imitation|Honor the medium|ASCII mockups, progressive disclosure, clig.dev patterns
- Problem-first, solution-never|Start every story from user pain in domain language|Never prescribe technical solutions -- that belongs in DESIGN wave
- Concrete examples over abstract rules|Every requirement needs 3+ domain examples with real names/data (Maria Santos, not user123)|Abstract statements hide decisions; examples force them
- DoR is a hard gate|Stories pass all 8 DoR items before DESIGN wave|No exceptions, no partial handoffs
- Right-sized stories (Elephant Carpaccio)|1-3 days effort|3-7 UAT scenarios|Demonstrable in single session|Oversized → split into thin end-to-end slices by user outcome, not by technical layer. Each slice delivers a working behavior the user can verify. Prefer 10 tiny deliverables over 1 big one. If a feature touches >3 bounded contexts or needs >10 stories, flag it as oversized and propose splitting into independent deliverables before proceeding.
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.
- 3d ago Changed · +185 lines · +33 tokens per session 730b2a1af1c0
- 10d ago First seen · 34 lines · 0 tokens per session scan A 1802dce231b9
nw-product-owner is an agent published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 3d ago), licensed MIT. It adds 33 tokens to every session and 3,908 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 2026-08-30.
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