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neqsim-compressor-power-screening

neqsim-compressor-power-screening is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 66 tokens per session (1,679 once invoked), scanned A, original, Apache-2.0.

A screening calculation for a single centrifugal-compressor stage. It estimates the compression energy, outlet gas temperature, and gas power from pressures, temperature, flow, and gas properties.

In plain words
What is it for?
Use it to scope a compression study, estimate polytropic head and discharge temperature, or check whether a proposed driver may be large enough.
Why use it?
It gives an early estimate before choosing a compressor or obtaining detailed vendor data. It can also compare estimated gas power with an available driver rating.

Skill for Claude CodeCodex

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

not rated 4repo changed 19d ago A scan 66 tokens original Apache-2.0

Good fit Use it to scope a compression study, estimate polytropic head and discharge temperature, or check whether a proposed driver may be large enough.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-compressor-power-screening
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-compressor-power-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-compressor-power-screening

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

agentmods 80×15 button for neqsim-compressor-power-screening

Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-compressor-power-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-compressor-power-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,679 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 $0.00066 $0.01679
Opus 5.5 $0.00026 $0.00672
Sonnet 5.5 $0.00013 $0.00336
Haiku 4.5 $0.00007 $0.00168

Measured 19d ago against content hash b9f37a0eca51, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-compressor-power-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 19d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (examples/basic_compressor_power_screening.py, src/compressor_power_screening/__init__.py, src/compressor_power_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/neqsim-compressor-power-screening/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Compressor Power Screening

Use this skill for public, educational centrifugal-compressor power screening. It estimates polytropic head, discharge temperature, and gas power for a single compression stage using the open polytropic-head equation so an agent can scope a compression study and check against a rated driver power before detailed selection.

When to Use

  • When a user asks roughly how much power a compression stage needs.
  • When an agent needs a quick polytropic-head and discharge-temperature estimate.
  • When examples must run without confidential compressor curves, vendor data, or company specs.

Inputs

  • suction_pressure: stage suction pressure P1 in bar absolute.
  • discharge_pressure: stage discharge pressure P2 in bar absolute.
  • suction_temperature: stage suction temperature T1 in kelvin.
  • mass_flow: gas mass flow in kg/s.
  • molecular_weight: gas molecular weight M in g/mol.
  • specific_heat_ratio: ratio of specific heats k, default 1.3.
  • compressibility: average compressibility factor Z, default 1.0.
  • polytropic_efficiency: polytropic efficiency, default 0.78.
  • rated_power: optional rated driver power in kW for the comparison.

Outputs

  • pressure_ratio: P2 / P1.
  • polytropic_head_kj_kg: polytropic head.
  • discharge_temperature_k: estimated discharge temperature.
  • gas_power_kw: gas power on the shaft.
  • power_margin_ratio: ratio of rated power to gas power, or null if no rated power supplied.
  • compressor_warning: ok, watch, over-rated, or no-rating.
  • assumptions: public assumptions used by the placeholder model.

Engineering Method

The Python class CompressorPowerModel uses the open polytropic-head equation only:

  • the polytropic exponent uses (n - 1) / n = (k - 1) / (k * polytropic_efficiency).
  • the polytropic head uses Hp = Z R T1 (n / (n - 1)) [(P2 / P1)^((n-1)/n) - 1], with R = 8.314 / M.
  • the discharge temperature uses T2 = T1 (P2 / P1)^((n-1)/n).
  • the gas power uses power = mass_flow * Hp / polytropic_efficiency.

Read the full file on GitHub · 137 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. 19d ago Changed · -1 lines b9f37a0eca51
  2. 1mo ago Changed · +1 lines 7f20fe4ac822
  3. 1mo ago First seen · 137 lines · 66 tokens per session scan A f9f83dc635ae

Subscribe to this mod's changes

neqsim-compressor-power-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 1,679 once invoked, about $0.0003 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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