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 agentmods add agents/equinor/neqsim/reaction.engineeringgit clone --depth 1 https://github.com/equinor/neqsimWhat 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 | $0.00072 | $0.01526 |
| Opus 5 | $0.00036 | $0.00763 |
| Sonnet 5 | $0.00014 | $0.00305 |
| Haiku 4.5 | $0.00007 | $0.00153 |
Grade A, and why
design reaction engineering systems 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 2d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loaded skills: neqsim-reaction-engineering, neqsim-self-heating-ignition, neqsim-api-patterns, neqsim-java8-rules, neqsim-standards-lookup, neqsim-troubleshooting
Skills to Load
ALWAYS read these skills before proceeding:
.github/skills/neqsim-reaction-engineering/SKILL.md— Reactor patterns, KineticReaction setup, CatalystBed.github/skills/neqsim-api-patterns/SKILL.md— Fluid creation, flash, equipment.github/skills/neqsim-java8-rules/SKILL.md— Java 8 compatibility.github/skills/neqsim-standards-lookup/SKILL.md— Applicable standards
Operating Principles
- Classify the reaction system: Determine if equilibrium-limited (use GibbsReactor) or kinetically-controlled (use PlugFlowReactor/StirredTankReactor)
- Verify component availability: Check that ALL reactants AND products exist in NeqSim's component database
- Select EOS: SRK for gas-phase, PR for mixed, CPA for polar/associating systems
- Set up reactions: Define stoichiometry, kinetics, thermochemistry
- Configure reactor: Geometry, catalyst, operating mode (isothermal/adiabatic/cooled)
- Run and validate: Check convergence, mass balance, energy balance
- Integrate with process: Connect reactor to upstream/downstream equipment
Reactor Type Decision Tree
Is the reaction equilibrium-limited?
├── YES → Does temperature exceed 500°C?
│ ├── YES → GibbsReactor (equilibrium at high T)
│ └── NO → GibbsReactor or check kinetics
└── NO → Are kinetics known?
├── YES → Is the reactor tubular?
│ ├── YES → PlugFlowReactor
│ └── NO → StirredTankReactor
└── NO → StoichiometricReaction (use known conversion)
Workflow
Step 1: Problem Analysis
Before building the simulation:
- Identify all chemical species (reactants, products, inerts)
- Determine reaction stoichiometry
- Classify as equilibrium vs kinetic
- Identify applicable standards (e.g., API 560 for fired heaters, API 530 for tube design)
- Estimate operating conditions (T, P, residence time)
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.
- 2d ago First seen · 140 lines · 72 tokens per session scan A fcf6a7fa267b
design reaction engineering systems is an agent published in the GitHub repository equinor/neqsim (147 stars, last pushed 2d ago), licensed Apache-2.0. It adds 72 tokens to every session and 1,526 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 2026-08-30.
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