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 noise-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/noise-screening)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/noise-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/noise-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/noise-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/noise-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 | $0.00076 | $0.01763 |
| Opus 5 | $0.00038 | $0.00881 |
| Sonnet 5 | $0.00015 | $0.00353 |
| Haiku 4.5 | $0.00008 | $0.00176 |
Grade A, and why
neqsim-noise-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.
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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Noise Screening
Use this skill to screen gas-valve and restriction noise at a stated receiver distance from either a representative operating measurement or a conservative energy model. Keep source prediction, receiver/workplace assessment, and acoustic-induced-vibration (AIV) screening as separate decisions.
When to Use
- When a user asks whether a gas valve or restriction is likely to be noisy.
- When current measured noise must be evaluated at a stated operating condition and receiver position.
- When an agent needs a quick action/high noise flag before detailed engineering.
- When examples must run without confidential valve trim or vendor noise data.
- Do not use this skill alone to accept personnel exposure, acoustic fatigue, or AIV.
Inputs
mass_flow: gas mass flow in kg/s.pressure_drop: pressure drop across the restriction in bar.inlet_density: inlet gas density in kg/m3.sound_speed: speed of sound in m/s (provide this, or temperature and molar mass).distance: source-to-receiver distance in m, default 1 m.measured_spl_at_distance: optional representative A-weighted measurement in dBA atdistance.measured_uncertainty_db: optional positive measurement uncertainty in dB.specific_heat_ratio: ratio of specific heatsk, default 1.3.temperature: gas temperature in K (used to estimate sound speed).molar_mass: gas molar mass in g/mol (used to estimate sound speed).- Constructor overrides for action level, high level, model uncertainty, acoustic efficiency, and transmission loss.
Outputs
vena_contracta_velocity_m_s: estimated velocity at the restriction.mach_number: velocity divided by the speed of sound.internal_sound_power_level_db: internal sound power level (re 1 pW).estimated_spl_1m_dba: screening sound-pressure level at 1 m.estimated_spl_at_distance_dba: assessed A-weighted level at the receiver distance.assessment_basis:measurementorscreening-model.noise_warning:ok,action, orhigh.uncertainty_db,standards_basis, andassumptionsfor review and escalation.
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.
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 · 145 lines · 76 tokens per session scan A f65493946ecb
neqsim-noise-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 76 tokens to every session and 1,763 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.
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