Jack Gross

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AI Extensions Digest: Anatomy, the skill that makes your agent build isometric machines

A two-week-old Agent Skill - MIT licensed, 17,000 stars - that turns a coding agent into an illustrator of working isometric machines in SVG and WebGL, with a geometry audit that proves its own drawings. I read the repo; I did not run it.

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AI Extensions
AI-generated illustration: AI Extensions Digest: Anatomy, the skill that makes your agent build isometric machines
AI-generated illustration

Today's find is a skill that makes your coding agent draw: Anatomy turns "explain how a rate limiter works" into a hand-built isometric machine in SVG, with WebGL fire when lines are not enough, and a self-check that proves no pipe passes through anything. Two weeks old and already past 17,000 GitHub stars.

The short version

Anatomy (github.com/wheresryan22/anatomy) is an Agent Skill - a folder with a SKILL.md at its root - that teaches Claude Code, Antigravity, OpenCode, Codex and MiniMax Code to build interactive isometric figures that explain technical ideas. MIT licensed (read from the LICENSE file), created October 8, 2026, observed October 20 at about 17,000 stars and 1,295 forks. No API keys, no npm dependencies beyond React for the optional components. I read the README, LICENSE and repository layout; I did not install or run it.

AI-generated illustration for the section: The short version
AI-generated illustration

What it is

Ask the agent for a figure that explains an idea, and Anatomy has it invent a physical object whose working is the concept: a cache key that skips work when nothing changed becomes a pin-tumbler lock that only turns when every pin matches; one GPU context serving many canvases becomes a gantry plotter visiting sixteen wells. The agent then builds that object from dozens of small shaded solids, painted back to front in an isometric camera, framed in a card with a title, a hint and a live readout, and set moving under the pointer and keyboard. Three output kinds share one kit: pure SVG (standalone HTML, a lone .svg, or React/Next.js components), SVG sandwiched around a WebGL shader layer for fire, water and glow, and a beta 3D mode where parts re-project and re-shade every frame as you drag. The committed examples - a Raptor engine that disassembles into eleven assemblies, a typing 1984 desk computer, a ripple tank - are built pages you can open directly.

The part that raises it above a drawing prompt is verification. A geometry audit proves nothing passes through anything, every end sits on a mount, and overlaps are drawn in depth order; headless Chrome takes screenshots and contact sheets; a lines check fails any stroke that ends in mid-air; and the skill instructs the agent to read every PNG it produces. In other words, the same loop a careful engineer applies to code - build, then attack your own work - applied to illustration.

Adoption, license, setup

The repository was created on October 8, 2026; when I checked on October 20 it had about 17,000 stars, 1,295 forks and 59 open issues - fast uptake even by agent-tooling standards. The LICENSE file is MIT, copyright "2026 Ryan". Installation is the standard Agent Skill shape: npx skills add wheresryan22/anatomy -g (the CLI asks which agents to set up, and wants Node 22.20 or later) or a plain git clone into the agent's skills folder; the whole kit is about 10 MB including the committed examples. There is nothing to npm install for the core - the drawing kit uses only Node's built-in modules - and no API keys beyond whatever agent you already run. The repo is the skill: SKILL.md holds the workflow and its rules, kit/ holds the isometric camera, solids, pipes, shaders and audits, references/ holds the long-form guides the agent opens on demand.

Limits and security notes

What it does not do: the 3D mode is explicitly beta, the densest example (the Raptor engine) takes minutes to build, and the self-checks need headless Chrome - which sandboxed agents may block. The README's Codex section is candid about this: the figure still gets built, only its checks fail, and it offers scoped fixes (approve the check command on request, or allow Chrome in the sandbox config) while warning that --sandbox danger-full-access "lifts every limit for that session, so keep it for projects you trust." That is the right instinct and worth quoting rather than paraphrasing. On privacy: the kit itself is local Node scripts with no network calls and no keys, so the data exposure is whatever your agent already sees - but as with any skill, you are handing an agent a standing instruction to write and execute build scripts and launch a browser, so install it where you would run that agent's code anyway. One governance note: the top contributor list shows the author plus a handful of small accounts, and the project is twelve days old; MIT-licensed or not, this is a single-maintainer project in its honeymoon phase, so pin a commit if you build on it.

Sources and limits

Read October 20, 2026: the GitHub repository page (stars, forks, issues, creation date), the raw LICENSE file (MIT), and the full README (install, usage, examples, how-it-works, limits sections). I did not install the skill, run any example, or verify the audit claims by execution - the figures and verification behavior above are the README's own description. Star and fork counts are point-in-time observations, not endorsements.