paperlab_scientific_traceability_audit

paperlab_scientific_traceability_audit is a skill for Claude Code, Codex from equinor/neqsim. It costs 56 tokens per session (800 once invoked), scanned A, original, Apache-2.0.

A review guide for PaperLab books, where technical chapters include calculations, figures, equations, notebooks, standards, or source documents. It checks whether important claims can be traced back to evidence and reproduced.

In plain words
What is it for?
Use it to audit scientific chapters, quantitative examples, figures, tables, equations, citations, and standards-based statements.
Why use it?
It helps expose unsupported numbers, unclear sources, missing units, and recommendations that lack evidence before publication or review.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to audit scientific chapters, quantitative examples, figures, tables, equations, citations, and standards-based statements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim/paperlab_scientific_traceability_audit
Install

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.

Any agent
npx skills add equinor/neqsim --skill paperlab_scientific_traceability_audit
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for paperlab_scientific_traceability_audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_scientific_traceability_audit/github.svg)](https://agentmods.dev/skills/equinor/neqsim/paperlab_scientific_traceability_audit)
Your own site
<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.

agentmods 80×15 button for paperlab_scientific_traceability_audit

Your own site · 80×15
<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>
Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 800 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash 433bc1ae22a7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.github/skills/paperlab_scientific_traceability_audit/SKILL.md · 105 lines

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_writing for NeqSim claim markers,
  • neqsim-notebook-patterns for executable notebooks,
  • neqsim-regression-baselines for stable examples,
  • neqsim_standard_requirement_extraction for 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

  1. Run book-skill-stack-plan and inspect traceability dimensions.
  2. Run book-evidence-check and book-figure-dossier.
  3. For each core chapter, identify the top 3 to 5 numerical or equation-based claims that deserve markers.
  4. Confirm every cited notebook exists and has executed output or generated figures.
  5. Confirm units in prose, tables, and figures match nomenclature.yaml.
  6. For standards-heavy chapters, add clause-level or paraphrased evidence rather than broad standard names.

Read the full file on GitHub · 105 lines

Changes

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.

  1. 1mo ago Changed · +1 lines 433bc1ae22a7
  2. 1mo ago First seen · 104 lines · 56 tokens per session scan A debf34c6d45a

Subscribe to this mod's changes

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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