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neqsim-pseudocomponent-split-characterization

neqsim-pseudocomponent-split-characterization is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 103 tokens per session (2,905 once invoked), scanned A, original, Apache-2.0.

A set of methods for dividing the heavy end of a reservoir fluid, such as the C7+ portion, into pseudocomponents—simplified components used to represent heavier hydrocarbons. It supports splitting, lumping, and rebuilding a detailed composition from a lumped one.

In plain words
What is it for?
Use it to split a C7+ fraction, calculate or apply a lumping factor, reconstruct detailed components, or prepare screening-level fluid cases for further NeqSim work.
Why use it?
It lets a fluid model use a controllable number of heavy components instead of requiring a separate detailed characterisation for every case. The split factor can also be adjusted when generating representative fluids.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 4repo changed 17d ago A scan 103 tokens original Apache-2.0

Good fit Use it to split a C7+ fraction, calculate or apply a lumping factor, reconstruct detailed components, or prepare screening-level fluid cases for further NeqSim work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization
View source ↗ equinor/neqsim-community-skills equinor.github.io
Install

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.

Any agent
npx skills add equinor/neqsim-community-skills --skill neqsim-pseudocomponent-split-characterization
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim-community-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for neqsim-pseudocomponent-split-characterization

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization/github.svg" alt="Measured on agentmods" height="20"></a>

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Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-pseudocomponent-split-characterization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,905 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.02905
Opus 5.5 $0.00041 $0.01162
Sonnet 5.5 $0.00021 $0.00581
Haiku 4.5 $0.00010 $0.00291

Measured 17d ago against content hash 1427d25b7c01, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 17d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (examples/split_example.py, src/pseudocomponent_split/__init__.py, src/pseudocomponent_split/pa_split.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/pvt/neqsim-pseudocomponent-split-characterization/SKILL.md · 236 lines

How it starts

The opening of the file, as written. The whole thing — 236 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:

  1. A Whitson three-parameter gamma molar split of a plus fraction (C7+), governed by a single split/characterization factor alpha.
  2. A lumping split factor computed from a detailed reference composition.
  3. 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), as in a universal paraffinic-aromatic 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+1 values give n pseudocomponents. The last boundary may be math.inf.
  • alpha: gamma shape / split factor (> 0; 1.0 = exponential heavy end).
  • eta: minimum molar mass of the distribution (g/mol).
  • full_composition and lumping_scheme for the split-factor / delumping path.

Read the full file on GitHub · 236 lines

Files

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.

Changes

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.

  1. 17d ago Changed · +1 lines 1427d25b7c01
  2. 18d ago Changed · +10 lines aa0f7223e529
  3. 19d ago Changed · -3 lines · -7 tokens per session 3b7f4c918341
  4. 1mo ago Changed · -34 tokens per session 75eb73df839b
  5. 1mo ago First seen · 228 lines · 144 tokens per session scan A e3d4c6272a88

Subscribe to this mod's changes

neqsim-pseudocomponent-split-characterization is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 103 tokens to every session and 2,905 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 2026-09-19.

Scientific
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