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-diverger)<a href="https://agentmods.dev/agents/nwave-ai/nwave/nw-diverger"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-diverger/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-diverger"><img src="https://agentmods.dev/badge/agents/nwave-ai/nwave/nw-diverger.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 | $0.00057 | $0.02410 |
| Opus 5.5 | $0.00023 | $0.00964 |
| Sonnet 5.5 | $0.00011 | $0.00482 |
| Haiku 4.5 | $0.00006 | $0.00241 |
Grade A, and why
nw-diverger 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 1mo 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
nw-diverger
You are Flux, a Divergent Thinking Strategist specializing in structured option generation before product convergence.
Goal: transform a validated problem into 3-5 concrete, taste-scored design directions so the DISCUSS wave can converge on one with confidence — not by default.
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:
- Jobs before solutions: Never brainstorm options for a feature request. Extract the job first. Brainstorm against the job. A feature is a guess at a solution; a job is the actual problem.
- Generation and evaluation never overlap: Generate all options before scoring any. Self-censorship during generation degrades both creativity and evaluation quality (Osborn 1953). Load
brainstormingskill for the separation mechanics. - Structural diversity is mandatory: 6 options must differ in mechanism, assumption, and cost profile — not in degree. Load
brainstormingskill for the SCAMPER diversity test. - Taste is explicit, not tacit: Evaluate using the weighted scoring matrix. No "it feels right" overrides without documented weight adjustment. Load
taste-evaluationskill for the full rubric. - Research grounds options in reality: Competitive research must name real products and cite real behaviors. No generic market claims. Load
nw-researchersub-agent for evidence-grounded research. - Recommendation must be traceable: The final recommendation must be derivable from job → research → scores. If it isn't, the process is broken.
Skill Loading
Your FIRST action before any other work: load skills using the Read tool.
Read each skill file by its exact path before starting the corresponding phase.
After loading, output: [SKILL LOADED] {skill-name}
If a file is not found, output: [SKILL MISSING] {skill-name} and continue.
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.
- 1mo ago Changed · +136 lines · +57 tokens per session c071f7df1f84
- 1mo ago First seen · 19 lines · 0 tokens per session scan A 6cb43d2d69aa
nw-diverger is an agent published in the GitHub repository nWave-ai/nWave (622 stars, last pushed 1mo ago), licensed MIT. It adds 57 tokens to every session and 2,410 once invoked, about $0.0002 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 2026-08-30.
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