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 acoustic-induced-vibration-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/acoustic-induced-vibration-screening)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/acoustic-induced-vibration-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/acoustic-induced-vibration-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/acoustic-induced-vibration-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/acoustic-induced-vibration-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 | $0.00093 | $0.01408 |
| Opus 5 | $0.00046 | $0.00704 |
| Sonnet 5 | $0.00019 | $0.00282 |
| Haiku 4.5 | $0.00009 | $0.00141 |
Grade A, and why
neqsim-acoustic-induced-vibration-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 12d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Acoustic-Induced Vibration Screening
Use this skill for public, educational acoustic-induced-vibration (AIV) screening of gas pressure-reducing devices. It estimates the generated sound power level, the pipe diameter-to-thickness ratio, an allowable sound power level, and a likelihood-of-failure (LOF) index so an agent can scope an AIV study before a detailed piping-vibration assessment. It complements the flow-induced-vibration-screening skill, which covers gas flow-induced vibration through a kinetic-energy index.
When to Use
- When a user asks whether a control valve, relief valve, or restriction orifice creates an AIV risk.
- When an agent needs a quick sound-power-level and LOF estimate downstream of a high pressure drop.
- When examples must run without confidential valve data, vendor noise curves, or company specs.
Inputs
mass_flow_kg_s: gas mass flow through the device in kg/s.upstream_pressure_bar: upstream pressureP1in bar absolute.downstream_pressure_bar: downstream pressureP2in bar absolute.pipe_outside_diameter_mm: downstream pipe outside diameter in mm.wall_thickness_mm: downstream pipe wall thickness in mm.molecular_weight: gas molecular weight, default 19.temperature_k: gas temperature in kelvin, default 313.15.downstream_pipe_length_m: downstream pipe length in m, default 10.sound_power_level_db: optional measured/known sound power level; if omitted it is computed.
Outputs
pressure_drop_ratio:(P1 - P2) / P1.sound_power_level_db: supplied or computed sound power level in dB.diameter_thickness_ratio: pipeD / t.allowable_sound_power_level_db: allowable sound power level from theD / tcorrelation.likelihood_of_failure: dimensionless AIV LOF index.downstream_pipe_length_m: echoed downstream pipe length.risk_warning:low-risk,medium-risk, orhigh-risk.assumptions: public assumptions used by the placeholder model.
Engineering Method
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.
- examples/basic_acoustic_induced_vibration_screening.py 1.1 KB runs code
- pyproject.toml 570 B
- README.md 1.1 KB
- src/acoustic_induced_vibration_screening/__init__.py 160 B runs code
- src/acoustic_induced_vibration_screening/model.py 5.8 KB runs code
- tests/test_acoustic_induced_vibration_screening.py 2.8 KB runs code
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.
- 12d ago First seen · 114 lines · 93 tokens per session scan A 27c24b375b4a
neqsim-acoustic-induced-vibration-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 1,408 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 2026-08-31.
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