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-root-whygit 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-root-why)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-root-why"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-root-why/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-root-why"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-root-why.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 | $0.00010 | $0.00849 |
| Opus 5.5 | $0.00004 | $0.00340 |
| Sonnet 5.5 | $0.00002 | $0.00170 |
| Haiku 4.5 | $0.00001 | $0.00085 |
Grade A, and why
nw-root-why 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 8d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code facts — resolve structural facts about code through
code-factCLI (vendor-neutral, bundled adapters: AST then TextSearch). Degrade LOUD. Never ad-hoc grep. Example:code-fact query.callers-of SYMBOL --root ROOT.
NW-ROOT-WHY: Toyota 5 Whys Root Cause Analysis
Wave: CROSS_WAVE Agent: Rex (nw-troubleshooter)
Overview
Systematic root cause analysis using Toyota's 5 Whys with multi-causal investigation and evidence-based validation. Investigates multiple cause branches at each level|validates solutions against all identified root causes.
Design-time counterexamples
RCA applies to design-time evidence at par with runtime failures: a
model-checker violation, a refuted invariant, a failing property, or a
theorem that only passes in conditional form. For these, the first RCA
question is representational — which type or schema made the failing state
expressible? A conditional theorem's hypothesis names the constraint the
design should enforce by construction. Route the cure through nw-design's
Counterexample discipline; a law added over an unchanged representation
without recorded justification is a symptom patch, not a root-cause fix.
This applies whether the counterexample came from a proof assistant, a
model checker, or a property test in the project's own language — no prover
is a prerequisite for this RCA question.
Agent Invocation
@nw-troubleshooter
Execute *investigate-root-cause for {problem-statement}.
Configuration:
- investigation_depth: 5
- multi_causal: true
- evidence_required: true
Usage: DELIVER Wave Retrospective (Phase 3.5)
When invoked as part of /nw-deliver Phase 3.5, execute in order:
- Analyze What Worked Well — Identify practices that succeeded and document why — preserve these. Gate: at least one practice documented with rationale.
- Analyze What Improved — Identify what worked better than before and why — record as reinforcements. Gate: delta from prior execution captured.
- Analyze What Worked Badly — Apply 5 Whys; the root cause names the producer/type that admitted the failing state (GDP-0) — a fix that adds a check instead is a symptom patch unless that producer cannot change, with the reason recorded. Gate: each failure has a representational root cause and fix.
- Analyze What Regressed — Apply 5 Whys to anything worse than before; produce prevention action. Gate: each regression has a root cause and prevention action.
- Tag Meta-Improvements — Mark any items requiring nWave framework changes as meta-improvements. Gate: all framework-level issues flagged.
- Append Retrospective — Write retrospective section to evolution document. If clean execution (no skips, no failures, no tooling issues), generate brief summary only. Gate: evolution document updated.
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.
- 8d ago Changed · +15 lines dbc831268c1c
- 2mo ago First seen · 66 lines · 10 tokens per session scan A f2f41f4ecfe7
nw-root-why is a skill published in the GitHub repository nWave-ai/nWave (634 stars, last pushed 4d ago), licensed MIT. It adds 10 tokens to every session and 849 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-09-06.
nw-root-why compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| nw-root-whynWave-ai/nWave | Skill | 634 | 4d ago | MIT | A | 10 | Claude Code |
| behavior-contracta5c-ai/babysitter | Skill | 1.9k | 10d ago | MIT | A | 25 | Claude Code |
| hk-rcadeepklarity/harness-kit | Skill | 105 | yesterday | MIT | A | 115 | Claude Code |
| debuggingInsajin/autopus-adk | Skill | 111 | 2mo ago | MIT | A | 16 | Claude Code, Codex |
| team-fixbostonaholic/team | Skill | 11 | yesterday | MIT | A | 30 | Claude Code, Codex |
| debug-flowDVNghiem/FlowDeck | Skill | 42 | 2mo ago | MIT | A | 34 | Claude Code, Codex |
| investigatevictusfate/scaffold | Skill | 7 | yesterday | MIT | A | 85 | Claude Code, Codex |