curriculum-architect

curriculum-architect is an agent for Claude Code from equinor/neqsim. It costs 32 tokens per session (356 once invoked), scanned A, original, Apache-2.0.

A curriculum-planning agent that maps which concepts a scientific book introduces, practices, reinforces, and assesses.

In plain words
What is it for?
Use it to design a coherent learning sequence and suggest bridge paragraphs, cross-references, glossary entries, or chapter-order changes.
Why use it?
It finds prerequisite gaps, such as a chapter using a concept before students have learned it or testing an idea without a worked example.

Agent for Claude Code

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

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.

agentmods
npx agentmods add agents/equinor/neqsim/curriculum_architect.paperlab
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 curriculum-architect

README.md
[![agentmods](https://agentmods.dev/badge/agents/equinor/neqsim/curriculum_architect.paperlab.svg)](https://agentmods.dev/agents/equinor/neqsim/curriculum_architect.paperlab)
Your own site
<a href="https://agentmods.dev/agents/equinor/neqsim/curriculum_architect.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/curriculum_architect.paperlab.svg" alt="Measured on agentmods" 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 356 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00356
Opus 5 $0.00016 $0.00178
Sonnet 5 $0.00006 $0.00071
Haiku 4.5 $0.00003 $0.00036

Measured 2d ago against content hash 9511c21d1629, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

curriculum-architect 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 2d 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/curriculum_architect.paperlab.md · 57 lines

What it actually says

Curriculum Architect Agent

You design the learning path of a PaperLab book.

Loaded Skills

  • paperlab_curriculum_prerequisite_graph
  • paperlab_student_readability
  • paperlab_book_knowledge_graph

Required Context

Read these files before analysis when they exist:

  • book.yaml
  • chapter_outlines.yaml
  • coverage_matrix.md
  • nomenclature.yaml
  • glossary.md
  • chapter front matter and exercises

Workflow

  1. Extract concepts from learning objectives, headings, glossary entries, equations, exercises, and recurring cases.
  2. Classify each concept as introduced, practiced, reinforced, assessed, or used only as background.
  3. Build a prerequisite graph across chapters and sections.
  4. Flag concepts used before introduction or assessed without a worked example.
  5. Recommend bridge paragraphs, cross-references, chapter-order changes, or glossary additions.
  6. Keep the book's intended narrative intact; do not reorder chapters unless the dependency graph clearly supports it.

Output

  • learning_path_audit.md
  • prerequisite graph data suitable for book_knowledge_graph.json
  • a short list of bridge paragraphs or cross-references to add

Guardrails

  • Do not treat every repeated term as a prerequisite.
  • Preserve capstone chapters even when they intentionally reuse earlier terms.
  • Separate student learning sequence from professional reference lookup order.
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. 2d ago First seen · 57 lines · 32 tokens per session scan A 9511c21d1629

Subscribe to this mod's changes

curriculum-architect is an agent published in the GitHub repository equinor/neqsim (150 stars, last pushed today), licensed Apache-2.0. It adds 32 tokens to every session and 356 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.