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.
npx skills add nWave-ai/nWave --skill nw-par-review-criteriagit 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/skills/nwave-ai/nwave/nw-par-review-criteria)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-par-review-criteria"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-par-review-criteria/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/skills/nwave-ai/nwave/nw-par-review-criteria"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-par-review-criteria.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00015 | $0.00875 |
| Opus 5 | $0.00008 | $0.00438 |
| Sonnet 5 | $0.00003 | $0.00175 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
nw-par-review-criteria 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 9d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DevOp Reviewer: Review Criteria
Critique Dimension 1: Incomplete Phase Handoffs
Pattern: Phase handoffs missing required artifacts or approvals.
Required per Phase:
- DISCUSS: Requirements document + peer review approval
- DESIGN: Architecture document + ADRs + peer review approval
- DISTILL: Acceptance tests + peer review approval
- DELIVER: Production code + tests (100% passing) + peer review approval
Severity: critical. Verify all artifacts present and peer-reviewed before phase transition.
Critique Dimension 2: Deployment Readiness Gaps
Pattern: Feature marked "ready" but missing production prerequisites.
Required: All tests passing (100%) | Production configuration complete | Monitoring/alerting configured | Runbook/operational docs created | Rollback plan documented.
Severity: critical. Complete missing prerequisite before marking deployment-ready.
Critique Dimension 3: Traceability Violations
Pattern: Cannot trace production code back to requirements.
Required: User stories map to acceptance tests | Acceptance tests map to production code | Code changes traceable to commits | All AC verified in production.
Severity: high. Establish traceability chain: user-story -> acceptance-tests -> code-commits.
Critique Dimension 4: Priority Validation
Purpose: Validate roadmap addresses largest bottleneck first, not secondary concern.
Questions
Q1: Is this the largest bottleneck? Does timing data show primary problem? Larger problem being ignored? Assessment: YES / NO / UNCLEAR.
Q2: Were simpler alternatives considered? Roadmap includes rejected alternatives? Rejection reasons evidence-based? Simpler solution achieves 80% benefit? Assessment: ADEQUATE / INADEQUATE / MISSING.
Q3: Is constraint prioritization correct? Constraints quantified by impact? Architecture addresses constraint-free opportunities first? Minority constraint dominating? (flag if >50% of solution for <30% of problem). Assessment: CORRECT / INVERTED / NOT_ANALYZED.
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.
- 9d ago First seen · 110 lines · 15 tokens per session scan A a3d162a7be92
nw-par-review-criteria is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 6d ago), licensed MIT. It adds 15 tokens to every session and 875 once invoked, about $0.0001 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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