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 --skill design-flash-benchmarkgit clone --depth 1 https://github.com/equinor/neqsimWrote 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/design-flash-benchmark)<a href="https://agentmods.dev/skills/equinor/neqsim/design-flash-benchmark"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/design-flash-benchmark/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/design-flash-benchmark"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/design-flash-benchmark.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 | $0.00016 | $0.01723 |
| Opus 5.5 | $0.00006 | $0.00689 |
| Sonnet 5.5 | $0.00003 | $0.00345 |
| Haiku 4.5 | $0.00002 | $0.00172 |
Grade A, and why
design-flash-benchmark 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 27d 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.
This is a copy
94% identical to design_flash_benchmark — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Design Flash Benchmark
Purpose
Create a structured test matrix for comparing flash algorithm performance across fluid types, thermodynamic conditions, and difficulty levels.
When to Use
- Starting a new flash algorithm comparison study
- Extending an existing benchmark to new fluid families
- Designing stress tests for near-critical or multi-phase regions
Benchmark Design Procedure
Step 1: Select Fluid Families
Choose from these standard families:
| Family | Components | Mole Fractions | Characteristics |
|---|---|---|---|
| Lean gas | CH4(0.90), C2(0.05), C3(0.03), N2(0.01), CO2(0.01) | Fixed or ±10% | Easy, mostly single-phase |
| Rich gas | CH4(0.70), C2(0.10), C3(0.08), nC4(0.05), nC5(0.03), N2(0.02), CO2(0.02) | Fixed or ±15% | Moderate, clear two-phase |
| Gas condensate | CH4(0.65), C2(0.08), C3(0.06), nC4(0.04), nC5(0.03), nC6(0.02), nC7(0.02), nC10(0.05), N2(0.02), CO2(0.03) | ±20% | Near-critical behavior |
| CO2-rich | CO2(0.80), CH4(0.10), N2(0.05), H2S(0.03), C2(0.02) | ±15% | Strong non-ideality |
| Wide-boiling | CH4(0.50), nC4(0.15), nC10(0.15), nC16(0.10), nC20(0.10) | ±20% | Large volatility range |
| Sour gas | CH4(0.60), CO2(0.15), H2S(0.10), C2(0.08), C3(0.05), N2(0.02) | ±15% | Acid gas behavior |
Step 2: Define PT Space
For each family, define the pressure-temperature sampling grid:
import numpy as np
def generate_pt_grid(T_min_K, T_max_K, P_min_bara, P_max_bara, n_T=20, n_P=20):
"""Generate a regular PT grid."""
T_values = np.linspace(T_min_K, T_max_K, n_T)
P_values = np.logspace(np.log10(P_min_bara), np.log10(P_max_bara), n_P)
cases = []
for T in T_values:
for P in P_values:
cases.append({"T_K": float(T), "P_bara": float(P)})
return cases
Standard ranges by family:
| Family | T range (K) | P range (bara) | Focus region |
|---|---|---|---|
| Lean gas | 200–400 | 1–200 | Dew point region |
| Rich gas | 220–450 | 5–300 | Two-phase dome |
| Gas condensate | 250–500 | 10–500 | Near cricondenbar |
| CO2-rich | 250–400 | 10–200 | CO2 critical region |
| Wide-boiling | 300–600 | 1–100 | Large T range |
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.
- 27d ago First seen · 165 lines · 16 tokens per session scan A c6349b949c9e
design-flash-benchmark is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 1,723 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to design_flash_benchmark, differing in 2 lines, and is treated as a copy.
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