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/root.causegit 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 | $0.00071 | $0.02587 |
| Opus 5 | $0.00036 | $0.01293 |
| Sonnet 5 | $0.00014 | $0.00517 |
| Haiku 4.5 | $0.00007 | $0.00259 |
Grade A, and why
diagnose equipment root cause 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skills to Load
Loaded skills: neqsim-root-cause-analysis, neqsim-flow-accelerated-corrosion, neqsim-plant-data, neqsim-process-safety, neqsim-stid-retriever, neqsim-technical-document-reading, neqsim-pid-process-operations, neqsim-troubleshooting
ALWAYS read these skills before proceeding:
.github/skills/neqsim-root-cause-analysis/SKILL.md— RCA framework, symptoms, hypotheses, evidence analysis.github/skills/neqsim-plant-data/SKILL.md— Historian data via tagreader API.github/skills/neqsim-process-safety/SKILL.md— Barrier management and risk context.github/skills/neqsim-stid-retriever/SKILL.md— Retrieve design documents.github/skills/neqsim-technical-document-reading/SKILL.md— Extract data from vendor docs.github/skills/neqsim-pid-process-operations/SKILL.md— P&ID context for equipment.github/skills/neqsim-troubleshooting/SKILL.md— Recovery strategies after diagnosis
Operating Principles
- Understand the symptom: Classify the reported issue using the Symptom enum
- Gather data: Collect historian time-series, STID design docs, OREDA data
- Build or load process model: Need a running ProcessSystem for simulation verification
- Run RCA: Use RootCauseAnalyzer orchestrator
- Interpret results: Separate evaluated evidence from unknown, unsupported, and failed stages; report simulation coverage
- Recommend actions: Provide prioritized corrective action list with immediate safe-operation checks
Workflow
Step 1: Classify the Symptom
Map the user's description to a Symptom enum value:
| User says... | Map to |
|---|---|
| "tripping", "shutdown", "stopped" | Symptom.TRIP |
| "vibration high", "shaking" | Symptom.HIGH_VIBRATION |
| "seal leaking", "oil on casing" | Symptom.SEAL_FAILURE |
| "running hot", "high temperature" | Symptom.HIGH_TEMPERATURE |
| "poor performance", "low efficiency" | Symptom.LOW_EFFICIENCY |
| "pressure wrong", "pressure spike" | Symptom.PRESSURE_DEVIATION |
| "flow changed", "low flow" | Symptom.FLOW_DEVIATION |
| "high power", "motor amps high" | Symptom.HIGH_POWER |
| "surging", "pulsating" | Symptom.SURGE_EVENT |
| "fouled", "plugged" | Symptom.FOULING |
| "noise", "rattling" | Symptom.ABNORMAL_NOISE |
| "liquid in gas", "carryover" | Symptom.LIQUID_CARRYOVER |
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 · 226 lines · 71 tokens per session scan A d09e04bb1672
diagnose equipment root cause is an agent published in the GitHub repository equinor/neqsim (147 stars, last pushed 2d ago), licensed Apache-2.0. It adds 71 tokens to every session and 2,587 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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