neqsim-adsorbent-capillary-condensation-screening

neqsim-adsorbent-capillary-condensation-screening is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 104 tokens per session (3,273 once invoked), scanned A, original, Apache-2.0.

An educational method for estimating when a contaminant vapour will condense inside an adsorbent bed, such as a molecular sieve or catalyst guard. It uses pore size and feed conditions to estimate a screening concentration limit.

In plain words
What is it for?
It is for screening methanol, water, glycol, heavy hydrocarbons, and similar contaminants before a fixed adsorbent bed.
Why use it?
It addresses cases where there is no visible liquid at the inlet but condensation inside tiny pores can still reduce the bed's effectiveness.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit It is for screening methanol, water, glycol, heavy hydrocarbons, and similar contaminants before a fixed adsorbent bed.

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Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/adsorbent-capillary-condensation-screening
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 adsorbent-capillary-condensation-screening
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-adsorbent-capillary-condensation-screening

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/adsorbent-capillary-condensation-screening/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/adsorbent-capillary-condensation-screening)
Your own site
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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.

agentmods 80×15 button for neqsim-adsorbent-capillary-condensation-screening

Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/adsorbent-capillary-condensation-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/adsorbent-capillary-condensation-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,273 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 $0.00104 $0.03273
Opus 5 $0.00052 $0.01636
Sonnet 5 $0.00021 $0.00655
Haiku 4.5 $0.00010 $0.00327

Measured today against content hash c54aecde17a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

neqsim-adsorbent-capillary-condensation-screening 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 today.

The scan reads SKILL.md. This mod also ships 4 executable files (examples/basic_adsorbent_capillary_condensation_screening.py, src/adsorbent_capillary_condensation_screening/__init__.py, src/adsorbent_capillary_condensation_screening/model.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/process/adsorbent-capillary-condensation-screening/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adsorbent Capillary Condensation Screening

Use this skill to turn a sorbent pore size into a contaminant concentration limit for the gas entering a fixed bed. It answers the question "how much methanol / water / heavy hydrocarbon can this feed carry before the bed stops working", which is a different and much tighter question than "when does a bulk liquid drop out".

When to Use

  • A mercury guard bed, molecular sieve, or catalyst guard bed is degrading and there is no free liquid at the inlet.
  • A feed specification has to be written for a condensable polar contaminant (methanol, water, glycol, heavy ends) upstream of an adsorbent.
  • An agent needs to explain why a "no free liquids" clause is not a sufficient specification.

The physics in one line

A concave meniscus in a pore condenses vapour below bulk saturation:

$$\ln a_c = -\frac{G,\gamma V_m\cos\theta}{r R T}$$

with $G = 2$ for cylindrical pores and $G = 1$ for slit pores. The bed limit is then $y_{max} = a_c \cdot y_{sat}$, where $y_{sat}$ is the bulk saturation mole fraction of the contaminant in the gas.

For methanol at 20 °C, $2\gamma V_m/RT = 0.75$ nm, so a 1.5 nm pore floods at 60 % of bulk saturation and a 6 nm pore at 88 %.

Inputs

  • temperature: gas temperature in kelvin.
  • surface_tension: contaminant liquid surface tension in N/m.
  • molar_volume: contaminant liquid molar volume in m³/mol.
  • pore_radius_nm: representative sorbent pore radius in nm.
  • saturation_mole_fraction: bulk saturation mole fraction $y_{sat}$ of the contaminant in the gas at bed T and P. Obtain this from a real equation of state, not from $P^{sat}/P$ — see the coupling note below.
  • contaminant_mole_fraction: optional current concentration, for a margin check.
  • contact_angle_deg: default 0 (perfect wetting, conservative).
  • geometry_factor: 2.0 cylindrical (default), 1.0 slit.

Outputs

  • kelvin_length_nm: $G\gamma V_m\cos\theta / RT$ in nm.
  • onset_relative_saturation: $a_c$.
  • max_mole_fraction / max_ppmv: the contaminant limit.
  • relative_saturation, margin_ratio: only when a current concentration is given.
  • kelvin_valid: false below ~2 nm radius, where Kelvin is non-conservative.
  • warning: ok, watch, or condensation-expected.
  • assumptions: the public assumptions applied.

Read the full file on GitHub · 259 lines

Files

What ships with it

6 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. today Changed · +56 lines c54aecde17a8
  2. 2d ago Changed · +46 lines b3b12c77e0fa
  3. 4d ago First seen · 157 lines · 104 tokens per session scan A 5fa889e7077e

Subscribe to this mod's changes

neqsim-adsorbent-capillary-condensation-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 104 tokens to every session and 3,273 once invoked, about $0.0005 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 2026-09-09.

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