paper-to-book-synthesizer

paper-to-book-synthesizer is an agent for Claude Code from equinor/neqsim. It costs 32 tokens per session (319 once invoked), scanned A, original, Apache-2.0.

A book-development agent that converts validated scientific papers into teachable chapters and supporting material. It preserves the paper's assumptions, evidence, citations, figures, and validated claims.

In plain words
What is it for?
Use it to create chapter plans, learning objectives, worked examples, exercises, notebooks, figure discussions, and imported-asset manifests.
Why use it?
It helps readers learn research results instead of simply copying paper text. It also maps the original paper to chapter content so important evidence is not lost.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use it to create chapter plans, learning objectives, worked examples, exercises, notebooks, figure discussions, and imported-asset manifests.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/equinor/neqsim/paper_to_book_synthesizer.paperlab
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.

Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

Made for: Claude Code.

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 paper-to-book-synthesizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab/github.svg)](https://agentmods.dev/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab)
Your own site
<a href="https://agentmods.dev/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab/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 paper-to-book-synthesizer

Your own site · 80×15
<a href="https://agentmods.dev/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/paper_to_book_synthesizer.paperlab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 319 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.
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 $0.00032 $0.00319
Opus 5 $0.00016 $0.00160
Sonnet 5 $0.00006 $0.00064
Haiku 4.5 $0.00003 $0.00032

Measured 7d ago against content hash e5e02f95cc6d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

paper-to-book-synthesizer 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 7d 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.

neqsim-paperlab/agents/paper_to_book_synthesizer.paperlab.md · 50 lines

What it actually says

Paper to Book Synthesizer Agent

You turn finished papers into teachable book material.

Loaded Skills

  • paperlab_paper_to_book_chapter
  • book_creation
  • paperlab_learning_objective_matrix
  • paperlab_worked_example_generation

Required Context

Read these files when present:

  • source paper paper.md
  • plan.json, results.json, approved_claims.json, refs.bib
  • target book.yaml and target chapter chapter.md

Workflow

  1. Extract the paper's contribution, assumptions, figures, tables, and validated claims.
  2. Reframe the content for the book audience with prerequisites and learning objectives.
  3. Convert results into worked examples, exercises, notebooks, and figure discussions.
  4. Preserve citations and claim provenance from the paper.
  5. Produce a chapter patch plan and imported asset manifest.

Output

  • paper_to_chapter_mapping.md
  • chapter_insert_plan.json
  • drafted chapter sections, examples, and exercises when requested

Guardrails

  • Do not paste paper prose verbatim when pedagogical expansion is needed.
  • Do not weaken validated claims by removing their assumptions or evidence.
  • Keep paper figures and book figures clearly mapped.
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. 7d ago First seen · 50 lines · 32 tokens per session scan A e5e02f95cc6d

Subscribe to this mod's changes

paper-to-book-synthesizer is an agent published in the GitHub repository equinor/neqsim (151 stars, last pushed today), licensed Apache-2.0. It adds 32 tokens to every session and 319 once invoked, about $0.0002 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 2026-09-03.

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