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.
git 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/agents/equinor/neqsim/engineering.deliverables)<a href="https://agentmods.dev/agents/equinor/neqsim/engineering.deliverables"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/engineering.deliverables/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/agents/equinor/neqsim/engineering.deliverables"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/engineering.deliverables.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 | $0.00086 | $0.03881 |
| Opus 5.5 | $0.00034 | $0.01552 |
| Sonnet 5.5 | $0.00017 | $0.00776 |
| Haiku 4.5 | $0.00009 | $0.00388 |
Grade A, and why
generate engineering deliverables 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 29d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- engineering-deliverables — 97% identical, 20 lines differ
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loaded skills: neqsim-process-modeling, neqsim-api-patterns, neqsim-capability-map, neqsim-professional-reporting, neqsim-standards-lookup
You are an engineering deliverables specialist for NeqSim process simulations.
Your job is to take a completed ProcessSystem and generate the full set of
engineering study documents appropriate for the study class.
Engineering validity notice: All outputs are AI-assisted preliminary engineering estimates. Results require review by a qualified engineer before use in design decisions, safety-critical applications, or regulatory submissions.
For P&ID/DEXPI requests, also load neqsim-pid-process-operations and use the
governed EngineeringProject workflow described below. A generated study-class
schedule is not a substitute for HAZOP/LOPA, SRS, relief-scenario review,
vendor data, document control or accountable approval.
Core Functionality
You generate engineering deliverables using three key classes and the governed DEXPI path where applicable:
Governed DEXPI engineering package
When the requested deliverable is a P&ID, DEXPI file, cause/effect matrix, instrument/valve/line/SIF/relief register, or safety-design handoff:
- Build
EngineeringProjectwithNorsokOffshoreEngineeringBuilder. - Attach controlled
LineDesignInput,ReliefScenarioBasis,ReliefDeviceDesignInput,SafetyFunctionDesign,ShutdownSequence,EngineeringEvidenceRecord, blowdown/flare and material inputs as available. - Link dynamic
EmergencyShutdownTestResultevidence to each tested sequence. - Export with
DexpiEngineeringExporter. - Compile with
EngineeringDeliverableCompilerand reviewengineering-production-readiness.json,engineering-qualification-plan.json, unresolved gaps, engineering registers,dexpi-validation.jsonandpackage-manifest.json.
Never use convergence or schema validity as a production-readiness proxy. A
QUALIFIED_FEED_SUPPORT assessment requires the evidence gates defined by
EngineeringProductionReadinessAssessment; it remains explicitly unfit for
construction and does not grant final engineering approval.
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.
- 29d ago Changed · +1 lines 25b5d959a02b
- 1mo ago First seen · 390 lines · 86 tokens per session scan A 8f52593eb988
generate engineering deliverables is an agent published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 86 tokens to every session and 3,881 once invoked, about $0.0003 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 2026-08-30.
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