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-community-skills --skill pseudocomponent-split-characterizationgit clone --depth 1 https://github.com/equinor/neqsim-community-skillsWrote 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-community-skills/pseudocomponent-split-characterization)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/pseudocomponent-split-characterization"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/pseudocomponent-split-characterization/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-community-skills/pseudocomponent-split-characterization"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/pseudocomponent-split-characterization.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 | $0.00144 | $0.02830 |
| Opus 5 | $0.00072 | $0.01415 |
| Sonnet 5 | $0.00029 | $0.00566 |
| Haiku 4.5 | $0.00014 | $0.00283 |
Grade A, and why
neqsim-pseudocomponent-split-characterization 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pseudocomponent Split-Factor Characterization
Use this skill to represent a reservoir fluid with a small, controllable number of adjustable factors instead of building a bespoke characterization for every fluid. It provides three plant-agnostic, dependency-free building blocks:
- A Whitson three-parameter gamma molar split of a plus fraction (C7+),
governed by a single split/characterization factor
alpha. - A lumping split factor computed from a detailed reference composition.
- A delumping reconstruction that turns a lumped composition back into detailed components using that split factor.
These are screening-level helpers. For design-grade work, move to the rigorous
NeqSim neqsim.thermo.characterization Java classes described below.
When to Use
- When a fluid must be described by detailed light components plus a heavy pseudocomponent set, and you want one factor to control the heavy-end split.
- When you have a reference fluid and want to generate representative or synthetic fluids by adjusting the split factor.
- When a lumped composition (few components) must be delumped back to a detailed composition using the internal distribution of a reference fluid.
- When you need a transparent, reproducible split before running the rigorous NeqSim characterization for design-grade work.
- When a fluid is represented on a universal Paraffinic-Aromatic (P/A) set (fixed 10 light + N paraffinic + N aromatic heavy lumps) and its heavy-end character is carried by a single split factor S (the paraffinic fraction of each heavy lump), per the Uleberg (2026) universal characterisation.
Inputs
z_plus: total mole fraction of the plus fraction, in(0, 1].m_plus: average molar mass of the plus fraction (g/mol).boundaries: increasing molar-mass boundaries (g/mol);n+1values givenpseudocomponents. The last boundary may bemath.inf.alpha: gamma shape / split factor (> 0;1.0= exponential heavy end).eta: minimum molar mass of the distribution (g/mol).full_compositionandlumping_schemefor the split-factor / delumping path.
What ships with it
8 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.
- examples/split_example.py 1.0 KB runs code
- pyproject.toml 609 B
- README.md 873 B
- src/pseudocomponent_split/__init__.py 1.4 KB runs code
- src/pseudocomponent_split/pa_split.py 18 KB runs code
- src/pseudocomponent_split/split.py 9.6 KB runs code
- tests/test_pa_split.py 5.1 KB runs code
- tests/test_split.py 2.2 KB runs code
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 First seen · 228 lines · 144 tokens per session scan A e3d4c6272a88
neqsim-pseudocomponent-split-characterization is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed today), licensed Apache-2.0. It adds 144 tokens to every session and 2,830 once invoked, about $0.0007 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 2026-08-31.
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