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-process-modelinggit 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-process-modeling)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-process-modeling"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-process-modeling/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-process-modeling"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-process-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00098 | $0.05087 |
| Opus 5.5 | $0.00039 | $0.02035 |
| Sonnet 5.5 | $0.00020 | $0.01017 |
| Haiku 4.5 | $0.00010 | $0.00509 |
Grade A, and why
neqsim-process-modeling 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 9d 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 — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NeqSim Process Modeling Skill
Build executable NeqSim process simulations from engineering descriptions. This skill is the process-flowsheet layer between thermodynamic fluid setup and downstream specialists such as mechanical design, safety, plant data, and reporting.
Use When
- Building a
ProcessSystemorProcessModelflowsheet from a process description. - Connecting equipment such as streams, separators, compressors, coolers, heaters, heat exchangers, pumps, valves, pipes, mixers, splitters, recycles, adjusters, and distillation columns.
- Extracting process results with units, compositions, duties, powers, phase splits, mass balances, energy balances, or equipment profiles.
- Preparing a steady-state process base case for mechanical design, relief sizing, flow assurance, dynamic simulation, plant-data comparison, or optimization.
Core Workflow
- Agree the model basis: engineering question, battery limits, feed/assay, units, product specifications, data provenance and required fidelity. Follow model-build-contract for every new or revised flowsheet; use its handoff checklist when another agent consumes it.
- Select the task pattern from oil-and-gas-task-patterns. Load only the relevant specialist skills. Discover additional capabilities rather than treating an equipment class name as proof of a validated application.
- Define fluids and feeds with the EOS/component sequence in
neqsim-api-patterns. Verify the EOS and phase options for the composition, pressure/temperature range and property being calculated. - Assemble a reusable builder with named streams/equipment, live outlet
connections, explicit terminal products and one
ProcessSystemper area. Return the process/plant and stream/equipment registries, not just numbers. - Solve progressively: establish the feed and once-through base case,
close physical recycles, then add adjusters and operating constraints. Use
makeRecycles()orsetAutoRecycles(true)for supported mixer/manifold loops. For coupled models, check the boolean fromrunUntilConverged(n)and retain residual/iteration evidence. A returnedrun()call is not convergence proof. - Validate each accepted case: external total/component balances, energy closure where heat/work matters, phase identity, feasible equipment limits, independent benchmark and repeat/nearby-point behavior. Missing evidence stays incomplete; never insert zero as a closure result.
- Deliver reusable outputs with explicit units, inputs, version, assumptions, data gaps, failed cases and validation evidence. Store notebooks/scripts in the task folder; publish sanitized examples only when requested.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago Changed · +13 lines 43f79bca0304
- 15d ago Changed · +19 lines 6b27d58b6c4b
- 27d ago Changed · +25 tokens per session d8a2072fc808
- 1mo ago Changed · +31 lines dec2b0bf5a45
- 1mo ago Changed · +52 lines 5ee5e55cf4ff
- 1mo ago First seen · 233 lines · 73 tokens per session scan A 9b6b434a1e9d
neqsim-process-modeling is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 98 tokens to every session and 5,087 once invoked, about $0.0004 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.
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