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 paperlab_scientific_traceability_auditgit 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/paperlab_scientific_traceability_audit)<a href="https://agentmods.dev/skills/equinor/neqsim/paperlab_scientific_traceability_audit"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_scientific_traceability_audit/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/paperlab_scientific_traceability_audit"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_scientific_traceability_audit.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 | $0.00056 | $0.00800 |
| Opus 5.5 | $0.00022 | $0.00320 |
| Sonnet 5.5 | $0.00011 | $0.00160 |
| Haiku 4.5 | $0.00006 | $0.00080 |
Grade A, and why
paperlab_scientific_traceability_audit 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- paperlab-scientific-traceability-audit — 98% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PaperLab Scientific Traceability Audit
When to Use
USE WHEN: a textbook chapter contains numbers, equations, figures, tables, or engineering recommendations that depend on calculations, simulations, standards, or source documents. This skill turns technical content into auditable content.
Pair with:
neqsim_in_writingfor NeqSim claim markers,neqsim-notebook-patternsfor executable notebooks,neqsim-regression-baselinesfor stable examples,neqsim_standard_requirement_extractionfor clause-level standards evidence.
Traceability Objects
Track six object types:
| Object | Required Evidence |
|---|---|
| Numeric claim | notebook cell, test, baseline, source table, or citation |
| Figure | source file, notebook, generated script, or approved source document |
| Equation | symbol definitions, units, source citation, and implementation link if used by NeqSim |
| Table | data source, units, and update path |
| Standard statement | standard code, revision, clause or paraphrased requirement |
| Recommendation | preceding evidence that supports the action |
Marker Rules
Use existing neqsim_in_writing markers for high-value NeqSim-backed content:
<!-- @neqsim:claim
test: src/test/java/neqsim/book/<book_slug>/<TestName>.java
baseline: src/test/resources/baselines/book/<book_slug>/<baseline>.json
-->
<!-- @neqsim:figure source=notebooks/<notebook>.ipynb cell=<cell-id-or-index> -->
<!-- @neqsim:eq method=neqsim.package.ClassName#methodName -->
Do not mark every sentence. Prioritize values and equations that students will reuse, cite, or compare in exercises.
Audit Workflow
- Run
book-skill-stack-planand inspect traceability dimensions. - Run
book-evidence-checkandbook-figure-dossier. - For each core chapter, identify the top 3 to 5 numerical or equation-based claims that deserve markers.
- Confirm every cited notebook exists and has executed output or generated figures.
- Confirm units in prose, tables, and figures match
nomenclature.yaml. - For standards-heavy chapters, add clause-level or paraphrased evidence rather than broad standard names.
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 Changed · +1 lines 433bc1ae22a7
- 1mo ago First seen · 104 lines · 56 tokens per session scan A debf34c6d45a
paperlab_scientific_traceability_audit is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 800 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 2026-09-03.
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