What is paperlab_book_knowledge_graph?

A review graph for a technical book that shows how chapters, figures, notebooks, standards, source folders, and skills are connected. It helps editors inspect the book's structure and evidence links.

Use it for gap analysis, traceability checks, duplicate-concept review, and visual maps of an editorial workflow.

It makes missing connections, isolated content, duplicate concepts, and figures without discussions easier to find. This supports targeted editorial review.

paperlab_book_knowledge_graph — Skill by equinor/neqsim

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_book_knowledge_graph

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_book_knowledge_graph/github.svg)](https://agentmods.dev/skills/equinor/neqsim/paperlab_book_knowledge_graph)

Your own site

<a href="https://agentmods.dev/skills/equinor/neqsim/paperlab_book_knowledge_graph"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_book_knowledge_graph/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/equinor/neqsim/paperlab_book_knowledge_graph"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_book_knowledge_graph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 415 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.00415
Opus 5.5	$0.00000	$0.00166
Sonnet 5.5	$0.00000	$0.00083
Haiku 4.5	$0.00000	$0.00042

Measured 1mo ago against content hash e53cfd6e03ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paperlab_book_knowledge_graph 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:

paperlab-book-knowledge-graph — 100% identical, 2 lines differ

neqsim-paperlab/skills/paperlab_book_knowledge_graph/SKILL.md · 53 lines

What it actually says

Skill: PaperLab Book Knowledge Graph

Purpose

Build a review graph for a PaperLab book so editors can see how chapters, figures, notebooks, standards, source folders, and skills connect. Use this when a book needs gap analysis, traceability review, duplicate-concept review, or a visual map of the editorial workflow.

Inputs

Use the book artifacts when they exist:

book.yaml
coverage_matrix.md
source_manifest.json
figure_dossier.json
standards_map.json
skill_stack_plan.json
chapter notebooks and figures

Workflow

Run the prerequisite audits: book-source-inventory, book-figure-dossier, book-standards-map, and book-skill-stack-plan.
Run python paperflow.py book-knowledge-graph <book_dir>.
Open book_knowledge_graph.html and review isolated nodes, missing skill links, figures without discussion, chapters without notebooks, and standards that appear in text but have no clause-level evidence.
Use the graph during adversarial review to decide which chapters need synthesis, source retrieval, or de-duplication.

Output

book_knowledge_graph.json with nodes[] and edges[].
book_knowledge_graph.html as a self-contained review page.

Review Questions

Does every figure-heavy chapter connect to technical_figure_understanding and figure-discussion?
Do equipment chapters connect to standards and safety skills?
Do notebook-heavy chapters have traceability markers?
Are case-study chapters connected to source documents and skills?

Safety Rules

Treat the graph as an editorial map, not proof of standards compliance.
Do not expose private source documents in a public graph; include only path labels and high-level source areas unless the source is public.
Regenerate after chapter order, figure, source, or standards-map changes.

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.

1mo ago First seen · 53 lines · 0 tokens per session scan A e53cfd6e03ba

Subscribe to this mod's changes

paperlab_book_knowledge_graph is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 415 tokens. 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.

Planning Scientific oil-and-gas phase-equilibrium physical-properties processing pvt thermodynamics

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens