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 equinor/neqsim --skill neqsim-self-heating-ignitiongit clone --depth 1 https://github.com/equinor/neqsimWrote 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/equinor/neqsim/neqsim-self-heating-ignition)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-self-heating-ignition"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-self-heating-ignition/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/equinor/neqsim/neqsim-self-heating-ignition"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-self-heating-ignition.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 | $0.00119 | $0.02540 |
| Opus 5.5 | $0.00048 | $0.01016 |
| Sonnet 5.5 | $0.00024 | $0.00508 |
| Haiku 4.5 | $0.00012 | $0.00254 |
Grade A, and why
neqsim-self-heating-ignition 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 20d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NeqSim Self-Heating and Spontaneous Ignition Skill
Screening for low-temperature self-heating leading to spontaneous ignition — the mechanism behind lagging fires, where a combustible liquid soaks into porous thermal insulation and ignites with no external ignition source.
When this skill applies
Reach for this skill when you see any of these signals:
- A fire or smoke event on insulated pipework, vessels or valves with no identified ignition source.
- A leak of a combustible liquid — glycol (MEG/DEG/TEG), heat-transfer oil, lubricating oil, hydraulic fluid, amine, diesel — onto or into porous insulation (mineral wool, glass wool, calcium silicate, perlite).
- Questions phrased as "can this liquid self-ignite?", "is this insulation safe?", "how thick can the lagging be?", "why did it catch fire hours after the leak stopped?"
- A request to interpret oven / basket / hot-storage test results, or to extrapolate small-scale test data to plant scale.
The one thing to get right
Self-heating is a size-dependent problem, not a temperature-only problem.
Heat is generated throughout the volume (scales with $r^3$) but lost through the surface (scales with $r^2$). So the same material at the same temperature can be perfectly stable as a thin film and ignite as a thick layer.
This is why the lumped adiabatic screening in
neqsim.process.safety.reaction.RunawayReactionAnalyzer cannot answer this
question — it assumes a well-stirred mass with no spatial conduction, so it has
no concept of a critical thickness or a critical surface temperature. Do not
substitute it. Use neqsim.process.safety.selfheating.
Equally, do not use a Gibbs/equilibrium calculation to decide whether something
self-ignites. GibbsReactor will report that any hydrocarbon is fully oxidised
to CO₂ and H₂O at 20 °C, because that is thermodynamically true and kinetically
irrelevant. Equilibrium gives you the fuel ($\Delta H$); only kinetics give you
the hazard.
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.
- 20d ago Changed · -43 tokens per session 617d63dbfc23
- 1mo ago First seen · 204 lines · 162 tokens per session scan A 9093c6a9c5c5
neqsim-self-heating-ignition is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 119 tokens to every session and 2,540 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…