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 --skill neqsim-literature-searchgit 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/skills/equinor/neqsim/neqsim-literature-search)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-literature-search"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-literature-search/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/neqsim-literature-search"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-literature-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.02112 |
| Opus 5.5 | $0.00033 | $0.00845 |
| Sonnet 5.5 | $0.00016 | $0.00422 |
| Haiku 4.5 | $0.00008 | $0.00211 |
Grade A, and why
neqsim-literature-search 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 today.
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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature & Web Search for Engineering Tasks
Find, store, and summarize related papers and web information for a NeqSim task
so the research is auditable, reusable, and distributable with the task
folder. This skill defines the workflow and storage convention; it pairs with
neqsim-stid-retriever (internal/vendor corpora), neqsim-technical-document-reading
(fact extraction), neqsim-pdf-ocr (scanned PDFs), and neqsim-standards-lookup
(which standards to pull). It is the open-literature/web counterpart to the
internal-document retrieval flow, and shares the same references/ collection
layout so everything lands in one distributable folder.
When to Use
- At the start of Step 1 (Scope & Research) on Standard/Comprehensive tasks.
- When the solver needs a reference for a claim, a correlation source, or an independent benchmark dataset (NIST, textbook worked examples, published lab data, standards).
- When background context from the web (method descriptions, equipment background, operator/vendor public material, regulatory text) informs scope.
Storage Convention (distributable, per-source)
All research is stored inside the task folder under
step1_scope_and_research/references/, filed by source so the collection can be
handed to others:
references/
├── SOURCES.md # human-readable summary (auto-generated)
├── collection_manifest.json # machine-readable record (auto-generated)
├── literature_findings.md # structured claims + citations from this search
├── literature/ # papers, standards, textbook PDFs
│ ├── Smith2019_CO2_dense_phase.pdf
│ └── NORSOK_M-001_2017.pdf
└── web/ # saved web pages / article extracts
├── nist_webbook_CO2_density.md
└── wikipedia_Joule-Thomson.md
- Papers / standards / textbook PDFs →
references/literature/. - Web pages →
references/web/, saved as a Markdown extract (title, URL, retrieval date, and the relevant text/tables) — NOT a raw HTML dump. Name files by source + topic (e.g.nist_webbook_CO2_density.md). - Never save research to workspace-level
output/orfigures/.
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.
- today Changed ff6bf8d85659
- 20d ago Changed · -21 tokens per session 1cc10d233407
- 1mo ago Changed · +16 lines cffe017cdbce
- 1mo ago First seen · 169 lines · 103 tokens per session scan A 468533bff9a6
neqsim-literature-search is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 82 tokens to every session and 2,112 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 2026-09-03.
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