neqsim-process-extraction

neqsim-process-extraction is a skill for Claude Code, Codex from equinor/neqsim. It costs 106 tokens per session (24,969 once invoked), scanned A, original, Apache-2.0.

A data-extraction guide for turning process descriptions, tables, PFDs (process flow diagrams), datasheets, and piping line lists into NeqSim's structured JSON or route models.

In plain words
What is it for?
Use it to prepare process simulations from design documents, extract P&ID operating changes, or build hydraulic pipeline routes from serial pipe segments.
Why use it?
It removes the manual work of converting inconsistent engineering documents into a format that a process simulation can read. It also helps preserve piping details such as elevations, connections, and minor losses.

Skill for Claude CodeCodex

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

Good fit Use it to prepare process simulations from design documents, extract P&ID operating…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim/neqsim-process-extraction
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 --skill neqsim-process-extraction
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

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-process-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-process-extraction.svg)](https://agentmods.dev/skills/equinor/neqsim/neqsim-process-extraction)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-process-extraction"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-process-extraction.svg" alt="Measured on agentmods" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 24,969 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 $0.00106 $0.24969
Opus 5 $0.00053 $0.12485
Sonnet 5 $0.00021 $0.04994
Haiku 4.5 $0.00011 $0.02497

Measured 3d ago against content hash 0b4a2295e218, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

neqsim-process-extraction 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 3d 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.

.github/skills/neqsim-process-extraction/SKILL.md · 2,203 lines

How it starts

The opening of the file, as written. The whole thing — 2,203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NeqSim Process Extraction Skill

Convert unstructured engineering information into the canonical NeqSim JSON format accepted by ProcessSystem.fromJson() and ProcessSystem.fromJsonAndRun().

Core Principle

Extract structured data into a constrained JSON schema. Do NOT write NeqSim Java/Python code.

The JSON schema is finite and well-defined. ProcessSystem.fromJson() handles all NeqSim API calls deterministically. Errors come back as structured, actionable messages.

P&ID operational workflow: When the source is a P&ID and the user asks about a valve action, active train, isolation boundary, bypass, drain, vent, or control-loop behavior, load neqsim-pid-process-operations. Extract both the steady-state topology and the model delta needed to simulate the action.

Exception for route hydraulics: When the source is a STID/E3D/P&ID/stress-isometric line-list table with serial pipe segments, use neqsim.process.equipment.pipeline.routing.PipingRouteBuilder rather than the generic JSON process builder. The route builder preserves line-list segment metadata, K-value minor losses, elevations, and explicit connection topology.

Architecture decision (MANDATORY): Before assembling JSON, classify the process complexity. Small/medium processes (≤ ~15 units, single recycle loop) use a single ProcessSystem. Large processes (multiple plant areas, cross-area recycles, different fluids) must be split into multiple ProcessSystem objects composed inside a ProcessModule, or use pre-built ProcessModuleBaseClass implementations. See Section 16 for the decision guide.


1. Target JSON Schema

Every extraction must produce JSON matching this format:

{
  "fluid": {
    "model": "SRK",
    "temperature": 323.15,
    "pressure": 65.0,
    "mixingRule": "classic",
    "multiPhaseCheck": false,
    "components": {
      "methane": 0.80,
      "ethane": 0.08,
      "propane": 0.05,
      "CO2": 0.03,
      "n-butane": 0.02,
      "nitrogen": 0.01,
      "n-pentane": 0.005,
      "n-hexane": 0.005
    }
  },
  "process": [
    {"type": "Stream", "name": "well stream", "properties": {"flowRate": [75000.0, "kg/hr"]}},
    {"type": "ThreePhaseSeparator", "name": "inlet separator", "inlet": "well stream"},
    {"type": "Compressor", "name": "export compressor", "inlet": "inlet separator.gasOut",
     "properties": {"outletPressure": 120.0, "isentropicEfficiency": 0.78}},
    {"type": "ThrottlingValve", "name": "letdown valve", "inlet": "inlet separator.oilOut",
     "properties": {"outletPressure": 15.0}}
  ],
  "autoRun": true
}

Read the full file on GitHub · 2,203 lines

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. 3d ago First seen · 2,203 lines · 106 tokens per session scan A 0b4a2295e218

Subscribe to this mod's changes

neqsim-process-extraction is a skill published in the GitHub repository equinor/neqsim (150 stars, last pushed today), licensed Apache-2.0. It adds 106 tokens to every session and 24,969 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 2026-09-03.

Related

Other skills, from other repositories

parsing-ccda-documents

Parses C-CDA / CCD XML clinical documents to extract human-readable section narrative plus coded entries, keyed by section LOINC codes and templateIds. Use before OpenMed processing when ingesting C-CDA R2.1 documents (CCD, Discharge Summary, H&P, Consultation Note) exported from an EHR and you need the narrative…

maziyarpanahi/openmed · 152 tokens

paper-plot-stub

Plot a results CSV (x, ybaseline, yours) as a two-line matplotlib chart and write a PDF. Demo-only.

opensquilla/opensquilla · 35 tokens

publication-chart-skill

This skill should be used when the user asks for a publication-quality scientific figure or table, wants help choosing the right chart for results, needs a paper-ready pubfig or pubtab workflow, wants a figure + companion table for a results section, wants an Excel sheet turned into publication-ready LaTeX, or wants…

Galaxy-Dawn/claude-scholar · 77 tokens

scholarly-publishing

Use when planning an end-to-end scholarly publishing workflow, including manuscript source-of-truth, submission assets, revision/rebuttal files, camera-ready checks, reproducible build expectations, and publication package structure.

foryourhealth111-pixel/Vibe-Skills · 47 tokens

slides-as-code

Build research slides with text-first source (Slidev/Marp/Reveal/Quarto) and reproducible export (PDF). Includes structure, figure reuse rules, and quality checklist for top-tier scientific presentations.

foryourhealth111-pixel/Vibe-Skills · 46 tokens

ts-paper-latex

Stage 7 (final assemble + compile) of the ts-paper suite. Assemble drafted LaTeX section bodies + refs.bib + blueprint into a compilable paper in the active TEMPLATE and compile it to PDF. Copies the template's .sty/.cls + assets, runs the deterministic template-driven post-processes (caption position, merge adjacent…

Spark-To-Paper-Skills/spark-to-paper-skills · 116 tokens