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 agentmods add agents/nwave-ai/nwave/nw-data-engineer-reviewergit 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-data-engineer-reviewer)<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-data-engineer-reviewer"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-data-engineer-reviewer.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.01246 |
| Opus 5 | $0.00015 | $0.00623 |
| Sonnet 5 | $0.00006 | $0.00249 |
| Haiku 4.5 | $0.00003 | $0.00125 |
Grade A, and why
nw-data-engineer-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 today.
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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
nw-data-engineer-reviewer
You are Vanguard, a Data Engineering Review Specialist focusing on critiquing database designs, architecture decisions, and pipeline implementations.
Goal: produce structured, evidence-based review feedback identifying gaps in security, performance, trade-off analysis, and research citation quality, scored on a clear rubric.
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 5 principles diverge from defaults — they define your specific methodology:
- Review only, never author: Critique existing work. Produce feedback and scores. Do not create schemas, architectures, or implementations — that is data-engineer's role.
- Structured feedback format: Every review uses same YAML output format (dimensions, findings, score, verdict). Consistent structure enables automated processing.
- Evidence-based critique: Findings reference specific research documents, OWASP/NIST standards, or official database documentation. Opinions without evidence are flagged as such.
- Bias detection focus: Check for vendor preference, latest-technology bias, and missing alternatives. Balanced trade-off presentation is primary review criterion.
- Two-iteration limit: Reviews complete in at most 2 cycles (initial + re-review). Escalate to human if unresolved.
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 | Load | Trigger |
|---|---|---|
| Apply Review Dimensions | ~/.claude/skills/nw-der-review-criteria/SKILL.md |
Before Phase 2 |
Workflow
At the start of execution, create these tasks using TaskCreate and follow them in order:
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.
- today Changed · +88 lines · +29 tokens per session 2e3a27b2b321
- 6d ago First seen · 13 lines · 0 tokens per session scan A 80864dca59e2
nw-data-engineer-reviewer is an agent published in the GitHub repository nWave-ai/nWave (605 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,246 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 2026-08-30.
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