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 reciprocating-compressor-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/reciprocating-compressor-screening)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/reciprocating-compressor-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/reciprocating-compressor-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/reciprocating-compressor-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/reciprocating-compressor-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 | $0.00075 | $0.01327 |
| Opus 5 | $0.00037 | $0.00664 |
| Sonnet 5 | $0.00015 | $0.00265 |
| Haiku 4.5 | $0.00007 | $0.00133 |
Grade A, and why
neqsim-reciprocating-compressor-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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reciprocating Compressor Screening
Use this skill for public, educational reciprocating-compressor screening. It estimates clearance volumetric efficiency, actual inlet capacity, the required number of stages, discharge temperature, and a rod-load utilisation ratio so an agent can scope a reciprocating-compression study before detailed selection.
When to Use
- When a user asks how many stages a reciprocating compressor needs or what its volumetric efficiency is.
- When an agent needs a quick actual-capacity and discharge-temperature estimate for a positive-displacement machine.
- When examples must run without confidential compressor data, vendor curves, or company specs.
Inputs
suction_pressure: stage suction pressureP1in bar absolute.discharge_pressure: final discharge pressureP2in bar absolute.suction_temperature: suction temperatureT1in kelvin.swept_volume_rate_m3_h: geometric (swept) volume rate in m3/h.clearance_fraction: cylinder clearance fractionC, default 0.12.specific_heat_ratio: ratio of specific heatsk, default 1.3.leakage_allowance: leakage/loss allowanceL, default 0.03.rated_rod_load_kn: optional rated rod load in kN for the rod-load comparison.piston_area_m2: optional piston area in m2 for the rod-load comparison.
Outputs
pressure_ratio: overallP2 / P1.stages: integer number of stages keeping each stage belowmax_stage_ratio.stage_pressure_ratio: per-stage pressure ratio.volumetric_efficiency: clearance volumetric efficiency.actual_inlet_capacity_m3_h: swept rate multiplied by volumetric efficiency.discharge_temperature_k: first-stage isentropic discharge temperature.rod_load_ratio: gas rod load divided by rated rod load, ornull.capacity_warning:ok,watch,low-volumetric-efficiency, ordischarge-temp-high.rod_load_warning:ok,watch,rod-load-exceeded, orno-rating.assumptions: public assumptions used by the placeholder model.
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_reciprocating_compressor_screening.py 1.1 KB runs code
- pyproject.toml 566 B
- README.md 1.0 KB
- src/reciprocating_compressor_screening/__init__.py 156 B runs code
- src/reciprocating_compressor_screening/model.py 6.5 KB runs code
- tests/test_reciprocating_compressor_screening.py 2.0 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.
- 11d ago First seen · 118 lines · 75 tokens per session scan A 3dd14d71f156
neqsim-reciprocating-compressor-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed today), licensed Apache-2.0. It adds 75 tokens to every session and 1,327 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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