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 neqsim-dynamic-process-preparationgit 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/neqsim-dynamic-process-preparation)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-dynamic-process-preparation"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-dynamic-process-preparation/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/neqsim-dynamic-process-preparation"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-dynamic-process-preparation.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 | $0.00062 | $0.01505 |
| Opus 5.5 | $0.00025 | $0.00602 |
| Sonnet 5.5 | $0.00012 | $0.00301 |
| Haiku 4.5 | $0.00006 | $0.00151 |
Grade A, and why
neqsim-dynamic-process-preparation 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 1mo 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dynamic Process Preparation
Use this skill when an agent must prepare a NeqSim ProcessSystem or multi-area ProcessModel for dynamic calculations. It focuses on model-readiness checks, mechanical-design handoff, equipment holdup and volume initialization, and the transient run sequence.
When to Use
- When a user asks to turn a steady-state NeqSim process into a dynamic-ready process.
- When a
ProcessSystemorProcessModelneeds equipment volumes, holdups, or initial liquid levels before transient simulation. - When an agent needs a documented workflow for
run(),storeInitialState(),setTimeStep(...), andrunTransient(). - When mechanical design should be estimated with NeqSim classes before dynamic calculations.
Inputs
process_name: public process or model name used in reports.process_kind:ProcessSystemorProcessModel.equipment: dynamic candidate equipment records withname,equipment_type, optionallength_m,diameter_m,liquid_level_fraction, andrequires_mechanical_design.time_step_seconds: proposed transient time step.total_time_seconds: optional total transient duration.initialization_basis: steady-state case, public design point, or synthetic example basis.
Outputs
dynamic_ready: boolean indicator for whether the supplied preparation metadata passes basic checks.equipment_actions: per-equipment actions such as enable dynamic mode, estimate mechanical design, set vessel geometry, and set initial level.estimated_volumes_m3: geometric cylindrical volume estimates for public readiness checks when dimensions are supplied.neqsim_sequence: NeqSim API sequence for initialization and transient execution.warnings: missing information or setup gaps that should be fixed before transient calculations.
Engineering Method
The Python class DynamicProcessPreparationModel is a public planning and validation helper. It does not run NeqSim itself. It checks that a dynamic-ready NeqSim workflow has the minimum metadata needed to initialize dynamic equipment and points the user to the NeqSim APIs that should do the real work.
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.
- 1mo ago First seen · 144 lines · 62 tokens per session scan A 523e6f0a6085
neqsim-dynamic-process-preparation is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 1,505 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-19.
neqsim-dynamic-process-preparation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neqsim-dynamic-process-preparationequinor/neqsim-community-skills | Skill | 4 | today | Apache-2.0 | A | 62 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 3d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |