Aqshalikhsan
IEEE-Access-Modular-Template
A modular LaTeX template for IEEE Access papers that separates each section into its own file and bundles the official class and fonts for out-of-the-box compilation.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It introduces a unique 'weaving' metaphor for note-taking, offers a built-in command set for gaps and warmth gauges, and includes an AI skill that can auto-generate full notebooks from a chapter.
Who it is for
- Students learning mathematics or technical subjects
- Educators who want to create active-learning handouts
- Self-learners who prefer paper-based active recall
- Latex users interested in aesthetic, dye-themed document design
Use cases
- Creating fill-in study guides for linear algebra, signal processing, or optimization
- Generating interactive proof skeletons for theorem-heavy courses
- Producing polished, illustrated notes with a woven cover and color-coded elements
- Using the AI skill to turn a textbook chapter into a ready-to-compile Loom notebook
Strengths
- Supports both passive reading and active fill-in exercises in one document via \fillin, \TODO, and yourturn environments
- Includes a warmth gauge (\warmth) and margin recall prompts (\recall) to track understanding
- Provides an AI skill that automatically generates Loom notebooks from source material
- Offers Overleaf-compatible editions and a template with comprehensive command reference
Considerations
- Requires XeLaTeX and specific macOS fonts (Optima, Songti, 楷体) for full visual fidelity; non-macOS users must modify font settings
- The AI skill is designed for Claude and may not work with other AI tools without adaptation
- Example notebooks are based on public-domain mathematics or follow copyrighted texts; users must ensure proper attribution for their own content
README quick start
🧶 Loom
Weave your understanding — a gorgeous XeLaTeX class for fill-in study notes
Notes you both read and fill: statements and intuition to take in, blanks and proof-skeletons to work out. Learn by active recall, on paper that looks like an illuminated manuscript.
Why Loom
Most notes are read-only: definition → theorem → proof, flowing past your eyes. You finish the page and remember nothing. Loom typesets the other layer too — the weave of your own understanding:
- 🧵 A page is cloth on a loom. Warp threads are the ideas in play (a left selvage rail). Knots are results that bind them (theorem boxes). Loose threads are your open questions. A warmth gauge records how well you actually grok each block.
- ✍️ Passive + active in one document. The exposition is written to be read;
the high-value steps are left blank (
\fillin), proofs ship as skeletons (\TODO), and the book's examples are restaged as "your turn" computations. The source is your answer key. - 🎨 Dyed in real pigments. Indigo, madder, weld, iron-gall — historical textile and ink dyes no maths template uses. Headings incised in Optima, body and math in Libertinus, 中文 in Songti/楷体. Every cover carries a procedurally-woven emblem.
- 🤖 An AI skill that writes them for you. Point Claude at a chapter and the
fill-in-notesskill produces a complete, compiling notebook in this style — organized around a spine, not transcribed.
Singular Value Decomposition — a definition knot, the geometry, a Your turn Fourier transform — the dictionary, the convolution theorem
Entropy — the information diagram, Gibbs' inequality Gradient descent — the rate, and the cost of conditioning
Concentration of measure — theorem stated, proof left as a skeleton Every device on one page (the demo)
Quickstart
git clone https://github.com/Polaris-Aeterna/loom-notes.git
cd loom-notes/template
latexmk -xelatex main.tex # or: xelatex main.tex (twice)
Then write. A blank starter, doubling as a live cheat-sheet of every command, is
in template/main.tex. Open the repo in VS Code and the
bundled .vscode/settings.json builds with XeLaTeX on
every save (LaTeX Workshop defaults to pdflatex, w
Description
A gorgeous XeLaTeX class + Claude skill for fill-in study notes — read and fill, learn by active recall.
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