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-stress-analysisgit 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-stress-analysis)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-stress-analysis"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-stress-analysis/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-stress-analysis"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-stress-analysis.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 | $0.00040 | $0.01026 |
| Opus 5 | $0.00020 | $0.00513 |
| Sonnet 5 | $0.00008 | $0.00205 |
| Haiku 4.5 | $0.00004 | $0.00103 |
Grade A, and why
nw-stress-analysis 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 3d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advanced Architecture Stress Analysis
Complexity science-based approach for architectures surviving unknown future stresses. Based on residuality theory by Barry M. O'Reilly (Former Microsoft Chief Architect, PhD Complexity Science).
Core paradigm: "Architectures should be trained, not designed."
When to Apply
Use for: high-uncertainty environments | mission-critical systems | complex socio-technical systems | innovative products | rapidly evolving markets
Skip for: well-understood stable domains | short-lived MVPs | simple few-component systems | resource-constrained environments
Three Core Concepts
1. Stressors
Unexpected events challenging operation. Categories: technical (failures, scaling, breaches) | business model (pricing shifts, competitive disruption) | economic (funding, market crashes) | organizational (restructuring, skill gaps) | regulatory (compliance changes) | environmental (infrastructure failures)
Brainstorm extreme and diverse. Goal = discovery, not risk assessment.
2. Residues
Design elements surviving after breakdown. Ask: "What's left when [stressor] hits?"
Example -- e-commerce under payment outage: residue = browsing, cart, wishlist. Lost: checkout, payment. Stress-informed: allow "reserve order, pay later."
3. Attractors
States systems naturally tend toward under stress. Differ from designed intent. Discovered through testing, not predicted.
Example -- social media under growth: designed = proportional scaling, actual attractor = read-heavy CDN mode (reads survive, writes queue/fail). Design for this.
Process
Step 1: Create Naive Architecture
Straightforward solution for functional requirements. No speculative resilience. Document as baseline.
Step 2: Simulate Stressors
Brainstorm 20-50 across all categories. Include extremes. Engage domain experts. Prioritize by impact (not probability).
Step 3: Uncover Attractors
Walk each stressor with experts. Ask "What actually happens?" Identify emergent behaviors. Recognize cross-stressor patterns.
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.
- 3d ago First seen · 92 lines · 40 tokens per session scan A 2b56e6f9d825
nw-stress-analysis is a skill published in the GitHub repository nWave-ai/nWave (610 stars, last pushed 4d ago), licensed MIT. It adds 40 tokens to every session and 1,026 once invoked, about $0.0002 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 2026-09-06.
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