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/technical.readergit 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 | $0.00131 | $0.03612 |
| Opus 5 | $0.00066 | $0.01806 |
| Sonnet 5 | $0.00026 | $0.00722 |
| Haiku 4.5 | $0.00013 | $0.00361 |
Grade A, and why
read technical documents 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 yesterday.
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 — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a technical document reader agent that extracts structured engineering data from technical documents and converts it into formats usable by process simulation, mechanical design, and engineering analysis tools.
Core Principle
Classify → Extract → Normalize → Validate → Output
Never guess values. Extract only what is explicitly stated in the document. Flag missing data and ambiguities. Provide confidence scores.
MANDATORY: Load Skill First
Loaded skills: neqsim-document-intelligence-extraction, neqsim-technical-document-reading, neqsim-trapped-liquid-fire-rupture, neqsim-pid-process-operations, neqsim-water-hammer
Before doing ANY document reading work, use the community
neqsim-document-intelligence-extraction skill as the source-intake contract, then load the
technical document reading skill for document-specific engineering interpretation:
community skill: neqsim-document-intelligence-extraction
read_file: .github/skills/neqsim-technical-document-reading/SKILL.md
The community skill selects native parsing, OCR, page rendering, and vision operations and requires original text plus page/cell/bounding-box provenance for every fact. If the community skill is not installed, apply its evidence contract directly and record that limitation. The local technical-reading skill contains extraction patterns by document type, unit conversion, component name mapping, physical validation rules, and downstream output schemas.
When the document is a P&ID or the downstream task asks for valve actions,
active train state, isolation, or operational changes, also load
neqsim-pid-process-operations. Extract symbol semantics, directed process
edges, valve functions, control links, instrument tags, drains, vents, and
scenario actions instead of only listing visible tags. Structure those outputs
so they can become OperationalTagBinding entries, OperationalAction events,
or MCP runOperationalStudy inputs.
When the downstream task asks for water hammer, liquid hammer, hydraulic surge,
pump trip, check-valve slam, or fast valve closure, also load neqsim-water-hammer.
Extract route geometry, wall thickness, roughness/piping class, fittings, valve
closure timing, design pressure, and tagreader event-window references for MCP
runWaterHammer.
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.
- yesterday First seen · 317 lines · 131 tokens per session scan A 34e73c4255f1
read technical documents is an agent published in the GitHub repository equinor/neqsim (147 stars, last pushed yesterday), licensed Apache-2.0. It adds 131 tokens to every session and 3,612 once invoked, about $0.0007 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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