This Tool Fixes Broken AI Diagrams

AI agents often lie when mapping your codebase. ask a coding agent to diagram a repo, and then you might see Kafka, Redis, or an API gateway that doesn't actually exist. These diagrams often look plausible, but they hallucinate components, rendering the entire visual untrustworthy and useless for real-world development. You cannot rely on visuals born from fiction.

Archify tackles this problem head-on. Its AI agent doesn't draw anything; instead, it describes the system as structured, typed JSON. This fundamental shift separates the system's precise description from its visual representation. Archify then validates this JSON rigorously before any diagram ever appears, ensuring accuracy from the ground up.

Think of Archify like LLVM for system maps. The AI coding agent acts as the frontend, generating the initial system description. That description becomes a validated JSON Intermediate Representation (IR), which must adhere to strict schemas. Only after passing these checks does a local compiler turn the IR into the final, interactive HTML, guaranteeing a multi-stage, verifiable output instead of guesswork.

Archify doesn't just let an AI "draw" a diagram. Instead, it demands the AI agent output a structured, typed JSON Intermediate Representation (IR). This IR then enters a rigorous, deterministic validation pipeline. Archify checks it against strict schemas and atomic gates for integrity, ensuring the system description holds up.

Crucially, bad JSON doesn't magically become a flawed diagram. If the graph is invalid, Archify fails the process, providing clear diagnostics and rule codes. This means you get error messages you can act on, rather than trusting a visual representation that's silently wrong. This "fail closed" approach builds foundational reliability.

Next, Archify adds a powerful layer of verifiable proof with its Repo Evidence feature. Nodes in a diagram can display an "SRC" badge. Click it, and you jump directly to the specific code, commit, and even the exact line range within your repository that proves the component's existence. The architecture is therefore provably true, not just plausible.

Consider tools like Mermaid: you can write syntactically correct diagram code, but it still might generate a diagram that's logically flawed or includes components not found in your actual codebase. Archify's comprehensive validation layer, coupled with its direct code-linking evidence, adds a critical dimension of semantic trust that other tools simply lack.

After Archify’s compiler validates the JSON, it produces a self-contained HTML file. This isn't a static image; it's an interactive system map that offers genuine utility. You can search for any service, instantly revealing its upstream and downstream dependencies. Then, interactively trace complex flows, like following a "cache miss" path through your entire system, step-by-step, instead of just staring at a static diagram.

For pull requests, the architecture diffing feature provides a crucial advantage. Archify compares two validated snapshots of your system, generating a visual "Before, Delta, After" comparison. This clearly highlights every architectural change: what components were added, removed, or rerouted, making code reviews far more robust and preventing unintended shifts.

While the interactive HTML file is the primary artifact and Archify's strongest feature, it offers robust export capabilities too. You can easily generate static images in formats like PNG, JPEG, WebP, SVG, and WebM. It also creates handy 1200x630 share cards for quick communication. But understand, these exports are secondary; the true value is in the dynamic, explorable HTML. For a deeper dive into Archify’s capabilities, visit its GitHub repository: tt-a1i/archify: Agent skill for beautiful, verifiable architecture, workflow, sequence, data-flow, and lifecycle diagrams—self-contained HTML with motion and crisp export. - GitHub.

Archify excels when you ask it specific, bounded questions. Avoid vague instructions like "map this repo"; that usually returns a load of garbage. Instead, ask a precise question, such as, "Diagram the user authentication flow for a cache miss," perhaps limiting it to 8-12 nodes for clarity and focus. This targeted approach ensures meaningful, validated output.

However, Archify is not a universal solution. It isn't ideal for simple diagrams embedded directly in GitHub READMEs, as GitHub does not render its interactive HTML output. The tool also requires an existing AI agent workflow using platforms like Claude Code or Cursor, integrating as an agent skill rather than a standalone app.

For high-stakes situations, Archify truly shines. Its validated, interactive output creates verifiable artifacts for crucial development stages. These include:

• Generating architecture diagrams for PR reviews, offering a clear delta of changes.
• Architecting new features within design documents.
• Establishing a reliable, commit-ready source of truth for system components in your repository.

This approach transforms diagrams from static images into trustworthy, editable system maps, making them an indispensable part of your engineering process.

What is Archify?

Archify is an open-source agent skill that enables AI coding agents like Claude to generate verifiable, interactive architecture diagrams. It works by having the agent produce a structured JSON representation of a system, which Archify then validates and compiles into a self-contained HTML file.

How does Archify prevent inaccurate diagrams?

Instead of letting an AI 'draw' an image, Archify enforces a strict validation pipeline. The AI must output a typed JSON graph that adheres to a schema. If the JSON is invalid or describes an impossible state, the process fails with clear diagnostics, preventing the creation of a misleading diagram.

What AI agents work with Archify?

Archify is designed as an agent skill and integrates with several popular coding assistants, including Claude Code, Cursor, Codex CLI, OpenCode, and DeepSeek Harness.

Is Archify a replacement for Mermaid?

For AI-generated, interactive, and verifiable diagrams used in PRs or design reviews, Archify offers superior features. However, for simple diagrams embedded directly in a GitHub README, Mermaid is often a more straightforward choice as its output is natively rendered by GitHub.