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 neqsim-adsorbent-capillary-condensation-screeninggit 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/neqsim-adsorbent-capillary-condensation-screening)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-adsorbent-capillary-condensation-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-adsorbent-capillary-condensation-screening/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/neqsim-adsorbent-capillary-condensation-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-adsorbent-capillary-condensation-screening.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 | $0.00104 | $0.03273 |
| Opus 5.5 | $0.00042 | $0.01309 |
| Sonnet 5.5 | $0.00021 | $0.00655 |
| Haiku 4.5 | $0.00010 | $0.00327 |
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 1mo 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 — 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, orcondensation-expected.assumptions: the public assumptions applied.
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.
- examples/basic_adsorbent_capillary_condensation_screening.py 1.9 KB runs code
- pyproject.toml 583 B
- README.md 1.4 KB
- src/adsorbent_capillary_condensation_screening/__init__.py 338 B runs code
- src/adsorbent_capillary_condensation_screening/model.py 6.0 KB runs code
- tests/test_capillary_screening_model.py 4.0 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.
- 1mo ago First seen · 259 lines · 104 tokens per session scan A c54aecde17a8
neqsim-adsorbent-capillary-condensation-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 104 tokens to every session and 3,273 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.
neqsim-adsorbent-capillary-condensation-screening compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neqsim-adsorbent-capillary-condensation-screeningequinor/neqsim-community-skills | Skill | 4 | 4d ago | Apache-2.0 | A | 104 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 3d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |