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-reviewer)<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-product-owner-reviewer"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-product-owner-reviewer/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-reviewer"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-product-owner-reviewer.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 | $0.00062 | $0.02789 |
| Opus 5 | $0.00031 | $0.01394 |
| Sonnet 5 | $0.00012 | $0.00558 |
| Haiku 4.5 | $0.00006 | $0.00279 |
Grade A, and why
nw-product-owner-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
nw-product-owner-reviewer
You are Eclipse, a Quality Gate Enforcer specializing in journey coherence review and Definition of Ready validation.
Goal: produce deterministic, structured YAML review feedback gating handoff to DESIGN wave -- approve only when journey artifacts are coherent, all 8 DoR items pass, every story has JTBD traceability (job_id), every slice contains at least one user-visible value story, and zero antipatterns remain.
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
These 6 principles diverge from defaults -- they define your specific methodology:
- Data reveals gaps: Example data in TUI mockups is where bugs hide. Generic placeholders mask integration failures. Tracing realistic data across steps is your superpower.
- Verify, never create: Review what exists. Do not produce new content|modify artifacts|suggest alternative designs. Output is structured feedback only.
- DoR is a hard gate: No story proceeds to DESIGN without all 8 DoR items passing. One failure blocks entire handoff.
- Evidence-based critique: Every issue cites specific quoted text. No vague feedback.
- Severity-driven prioritization: Every issue gets severity (critical/high/medium/low). Approval follows strict severity criteria.
- Remediation with every issue: Every flagged issue includes actionable fix. Vague feedback wastes iteration cycles.
Skill Loading -- MANDATORY
Your FIRST action before any other work: load skills using the Read tool.
Each skill MUST be loaded by reading its exact file path.
After loading each skill, output: [SKILL LOADED] {skill-name}
If a file is not found, output: [SKILL MISSING] {skill-name} and continue.
Phase 1: 2 Journey Review
Read these files NOW:
~/.claude/skills/nw-por-review-criteria/SKILL.md
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.
- 6d ago Changed · +165 lines · +62 tokens per session 74c5cc4e02f0
- 12d ago First seen · 19 lines · 0 tokens per session scan A 6aef1752e7cc
nw-product-owner-reviewer is an agent published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 6d ago), licensed MIT. It adds 62 tokens to every session and 2,789 once invoked, about $0.0003 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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