What is neqsim-control-valve-cv-screening?

A screening aid for estimating a control valve’s required flow coefficient, called Kv or Cv, for liquid or gas service. It also checks for choked flow, where increasing the pressure drop no longer increases flow.

Use it to estimate Kv/Cv and check choked-flow risk from pressures, flow, and fluid properties before choosing a control valve.

It gives an early estimate before detailed valve selection, without needing vendor curves or confidential specifications. It can also flag possible flashing or critical gas flow.

neqsim-control-valve-cv-screening — Skill for Claude Code and Codex by

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 control-valve-cv-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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/control-valve-cv-screening/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/control-valve-cv-screening)

Your own site

<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/control-valve-cv-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/control-valve-cv-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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/control-valve-cv-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/control-valve-cv-screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,459 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.

Model	Per session	Once invoked
Fable 5.1	$0.00081	$0.01459
Opus 5	$0.00041	$0.00730
Sonnet 5	$0.00016	$0.00292
Haiku 4.5	$0.00008	$0.00146

Measured 11d ago against content hash 7fd1c6167955, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

neqsim-control-valve-cv-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 11d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (examples/basic_control_valve_cv_screening.py, src/control_valve_cv_screening/__init__.py, src/control_valve_cv_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/control-valve-cv-screening/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Control Valve Cv Screening

Use this skill for public, educational control-valve sizing screening. It estimates the required flow coefficient (Kv and Cv) and flags choked flow for liquid and gas service using the open IEC 60534-2-1 / ISA-75.01 equations so an agent can scope a valve and decide whether to invoke validated NeqSim valve calculations.

When to Use

When a user asks roughly what Cv a control valve needs for a duty.
When an agent needs a quick choked-flow (flashing or critical) flag.
When examples must run without confidential valve data, vendor curves, or company specs.

Inputs

Common:

service: "liquid" or "gas".
inlet_pressure: valve inlet pressure P1 in bar absolute.
pressure_drop: valve pressure drop dP in bar.
rated_cv: optional rated valve Cv for the margin check.

Liquid service:

flow_rate: volumetric flow in m3/h.
specific_gravity: liquid specific gravity (water = 1).
vapor_pressure: fluid vapor pressure in bar absolute, default 0.
critical_pressure: fluid critical pressure in bar absolute (for FF), optional.
fl: liquid pressure-recovery factor FL, default 0.9.

Gas service:

mass_flow: gas mass flow in kg/h.
inlet_density: inlet gas density in kg/m3.
specific_heat_ratio: ratio of specific heats k, default 1.3.
xt: pressure-drop-ratio factor xT, default 0.7.

Outputs

service: the resolved service.
required_kv: required flow coefficient in metric Kv.
required_cv: required flow coefficient in US Cv (1.156 * Kv).
choked: choked-flow flag.
choke_limit: choked pressure drop in bar (liquid) or choking x (gas).
cv_margin_ratio: rated_cv / required_cv, or null if no rating.
valve_warning: ok, watch, under-sized, choked, or no-rating.
assumptions: public assumptions used by the placeholder model.

Engineering Method

The Python class ControlValveCvModel uses public IEC 60534-2-1 / ISA-75.01 equations:

liquid Kv uses Kv = Q * sqrt(SG / dP_sizing).
the liquid liquid-critical-pressure-ratio factor uses FF = 0.96 - 0.28 * sqrt(Pv / Pc).
liquid choke occurs when dP >= FL^2 * (P1 - FF * Pv); the sizing dP is capped at this limit.
gas uses x = dP / P1, Fk = k / 1.4, choke x = Fk * xT, expansion factor Y = 1 - x / (3 Fk xT) bounded to [0.667, 1], and the mass-flow form Kv = W / (N6 * Y * sqrt(x * P1 * rho1)) with N6 = 27.3.
Cv = 1.156 * Kv.

Read the full file on GitHub · 128 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.

11d ago First seen · 128 lines · 81 tokens per session scan A 7fd1c6167955

Subscribe to this mod's changes

neqsim-control-valve-cv-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 81 tokens to every session and 1,459 once invoked, about $0.0004 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 2026-08-31.

Scientific

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens