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neqsim-benchmark-reference-data

neqsim-benchmark-reference-data is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 117 tokens per session (3,913 once invoked), scanned A, original, Apache-2.0.

A reference-data registry and comparison helper for checking NeqSim results against independent published measurements and standards. It records where each reference value came from, its valid range, uncertainty, and acceptance limit.

In plain words
What is it for?
Use it when validating fluid properties, critical constants, or saturation conditions, and when producing benchmark results for notebooks, reports, or automated checks.
Why use it?
It prevents benchmark reports from using unexplained numbers, weak citations, or arbitrary tolerances. It makes validation comparisons traceable and repeatable.

Skill for Claude CodeCodex

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

not rated 4repo changed 27d ago A scan 117 tokens original Apache-2.0

Good fit Use it when validating fluid properties, critical constants, or saturation conditions, and when producing benchmark results for notebooks, reports, or automated checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data
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-benchmark-reference-data
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-benchmark-reference-data

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data/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.

agentmods 80×15 button for neqsim-benchmark-reference-data

Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-benchmark-reference-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,913 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 $0.00117 $0.03913
Opus 5.5 $0.00047 $0.01565
Sonnet 5.5 $0.00023 $0.00783
Haiku 4.5 $0.00012 $0.00391

Measured 27d ago against content hash 0670fef89c64, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-benchmark-reference-data 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 27d ago.

The scan reads SKILL.md. This mod also ships 13 executable files (examples/validate_against_anchor_points.py, examples/validate_with_coolprop.py, src/benchmark_reference_data/__init__.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-benchmark-reference-data/SKILL.md · 312 lines

How it starts

The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Benchmark Reference Data

Every Standard and Comprehensive NeqSim task must compare its results against independent reference data before the numbers are reported. In practice that step gets rewritten in every benchmark notebook, with the reference values pasted in as bare literals, no citation, an invented tolerance, and no check that the reference is actually independent of the model being tested.

This skill supplies the parts that should not be rewritten: where the reference came from, whether it is allowed to be used as a benchmark here, how far the model may deviate before the comparison fails, and what the result block must look like so the report generator and the CI gate accept it.

It does not compute NeqSim results. It provides the other side of the comparison and the verdict.

When to Use

  • A task is writing its XX_benchmark_validation.ipynb notebook.
  • A benchmark_validation block must be produced for results.json.
  • A property, critical constant, or saturation condition from a NeqSim fluid needs an independent, citable reference value.
  • A number quoted in a report needs a traceable provenance chain from value to citation.
  • An existing benchmark claim must be audited: is the reference independent, is the deviation larger than the reference's own uncertainty, are there enough points?

When Not to Use

  • As a property engine. CoolProp and the anchor table are references, not the model — do not use them to produce the answer the task is asked for.
  • For mixtures outside a reference formulation's validated range. The applicability gate will refuse, and it is right to refuse.
  • As a substitute for measured data on the actual fluid. A reference EOS for a pure component does not validate a characterised reservoir fluid; it validates the pure-component limit of the model.
  • To manufacture a PASS. Loosening the tolerance until a comparison passes is the failure mode this skill exists to make visible.

Inputs

Input Meaning
model_value the number the task computed (NeqSim, or any model under test)
reference a ReferencePoint from the anchor table or the CoolProp backend
tolerance_pct acceptance band in percent; defaults per property when omitted
model_tier authority tier of the model basis, default "correlation"
model_label label used in the output block, default "neqsim"
informational mark a comparison as context only, never graded

Read the full file on GitHub · 312 lines

Files

What ships with it

15 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. 27d ago Changed · +6 lines 0670fef89c64
  2. 1mo ago Changed · +7 lines · -103 tokens per session daa4355109c3
  3. 1mo ago First seen · 299 lines · 220 tokens per session scan A 848e7c8e8ff1

Subscribe to this mod's changes

neqsim-benchmark-reference-data is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 117 tokens to every session and 3,913 once invoked, about $0.0005 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.

Analytics and metricsScientific
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