As autonomous AI coding assistants (such as Claude Code, Cursor, and Codex CLI) become central to system design, engineering teams increasingly use them to map complex architectures. However, typical AI-drawn diagrams suffer from inconsistent geometry, untyped syntax errors, and an inability to track structural changes across Git revisions.
Archify is an open-source diagramming and validation engine developed by tt-a1i to bring rigor to AI-generated system maps. Rather than generating loose markdown charts, Archify
requires AI agents to produce a typed JSON Intermediate Representation (IR) that compiles deterministically into interactive, self-contained HTML and SVG artifacts.
Archify
operates as a verification engine and rendering compiler. When you ask an AI agent to map a codebase or design a cloud architecture, the agent outputs a structured JSON schema. Archify
validates node clearances, boundary crossings, and layout hierarchies before generating a complete, standalone visual artifact.
Archify supports five core technical visualization models:
During pull request reviews or system refactors, Archify supports side-by-side snapshot diffing. Developers can compare Before, Delta, and After states to inspect exact added, removed, moved, or rerouted components with a deterministic verification receipt.
Archify outputs self-contained HTML files with advanced interactive capabilities:
R
):F
):Archify installs seamlessly across modern AI coding environments:
npx skills add tt-a1i/archify -g
npx -y skills add tt-a1i/archify --skill archify --agent cursor --global --copy --yes
By combining typed JSON validation with deterministic vector compilation, Archify
transforms natural language system descriptions into trustworthy, publication-ready architecture diagrams. It is an indispensable tool for senior engineers and system architects pair-programming with AI agents.
Want to turn your architecture descriptions into verifiable system maps? Check out the Archify GitHub Repository.