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DD

cathrynlavery/diagram-design

AI Agent

29 editorial diagram types for Claude Code. Self-contained HTML + SVG. No shadows, no Mermaid-slop.

19k Stars1.1k Forks19 Open Issues19k WatchersHTMLMIT
AI AgentAI AppDeveloper ToolData Tool
Review Readiness

This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.

100

review score

Indexable review
Decision Snapshot

Problem solved

It solves the problem of AI-generated diagrams looking generic and unpolished, which often forces users to spend time in Figma or skip diagrams entirely. By providing a curated set of editorial visual types and automatic brand matching from a website URL, it delivers high-quality, consistent diagrams in seconds without manual styling.

Deployment reality

The available setup signal starts with: pi install https://github.com/cathrynlavery/diagram-design. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.

Commercial use

The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.

Capability ceiling

Developers can generate architecture diagrams, flowcharts, sequence diagrams, state machines, ER models, timelines, swimlanes, quadrant charts, org charts, Venn diagrams, layer stacks, pyramids, radar charts, loops, IT current-state maps, and more—all as static HTML+SVG that can be opened directly in a browser. The skill supports semantic patterns for behavior (queue, policy trace, trust boundary) and can convert existing draw.io/Mermaid sources, making it suitable for documentation, technical blog posts, internal wikis, and client deliverables. The ceiling includes fully customized, brand-aligned diagrams with optional motion for ordered explanations, all without external dependencies.

Source and compliance noteLast synced: Aug 16, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy
Editorial Evaluation

cathrynlavery/diagram-design is tracked as a HTML project in the AI Agent, AI App, Developer Tool, Data Tool area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.

Momentum check: the repository has 19k total stars, with +1.6k today, +15k this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.

Maintenance check: current activity is Active; the latest push was 8 days ago, and the open issue queue is 19, about 0.10% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.

Adoption check: 1.1k forks and 19k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.

Practical fit: this project is most relevant when you need HTML teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.

Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 15k. Follow the original GitHub repository for final install, security, and release information.

Evidence Checklist

Analysis

Ready

Original problem, capability, and verdict guidance are available.

Sources

Ready

Repository metadata and README/source references are attached.

License

Ready

MIT is recorded for review.

Maintenance

Ready

Recent activity is visible in repository metadata.

Alternatives

Ready

Enough nearby projects exist for comparison.

Best For
  • HTML teams evaluating ecosystem-native tooling
  • teams that prefer mature projects with broad adoption signals
  • use cases where recent maintenance matters
Avoid When
  • you need a legal review, security audit, or production SLA
Adoption Signals

Momentum

19k Stars

Reuse

1.1k Forks

Attention

19k Watchers

Maintenance

active

License

MIT

Open issues

19

Overview

Diagram Design is a skill for AI coding agents (Claude Code, Codex, Pi) that generates editorial-quality diagrams in 27 visual types, matching a brand's style by reading its website. It outputs static HTML by default with optional accessible motion, and can redraw draw.io or Mermaid sources.

Key Features

- 27 visual types including architecture, flowchart, sequence, state machine, ER, timeline, swimlane, quadrant, nested, tree, org chart, Venn, layers, pyramid, consultant 2×2, radar, loop, IT current-state, high-level, bar, line, Gantt, scatter, process, medallion, data flow, DP integration, and DP security matrix. - Three static variants (minimal light, minimal dark, full-editorial) with no build step or external dependencies. - One agent skill for Claude Code, Codex, and Pi; semantic patterns describe behavior separately from layout; optional motion for ordered explanations.

Tool Positioning

AI Agent

Agent frameworks, autonomous workflows, and tool-use systems

AI App

End-user AI applications and AI-native product examples

Developer Tool

Tools that improve coding, testing, build, and local workflow

Data Tool

Databases, data pipelines, ETL, analytics, and vector search

Quick Start
pi install https://github.com/cathrynlavery/diagram-design
View on GitHub
Project Activity

80

Health Score

Active

Commit Activity

Apr 16, 2026

Created

Aug 14, 2026

Last push

Source Trail

GitHub repository metadata

metadata

GitHub README

readme_summary

Star History

+1.4k

Today's growth

+8.3k

7-day growth

+8.3k

30-day growth

Aug 13, 2026Aug 16, 2026
Community Health
1.1k

Forks

19

Open

19k

Watchers

Owner
DD

cathrynlavery

GitHub profile
Topics & Language
HTML
Ecosystem & Usage
GitHub Repository
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License
MIT
CreatedApr 16, 2026
Last pushAug 14, 2026
Last syncedAug 16, 2026
Repository Standards

✓

License

✓

Forked

✓ Active

Maintained

AI AnalysisAnalyzed by Git-Stars

Problem Solved

It solves the problem of AI-generated diagrams looking generic and unpolished, which often forces users to spend time in Figma or skip diagrams entirely. By providing a curated set of editorial visual types and automatic brand matching from a website URL, it delivers high-quality, consistent diagrams in seconds without manual styling.

Capabilities

Developers can generate architecture diagrams, flowcharts, sequence diagrams, state machines, ER models, timelines, swimlanes, quadrant charts, org charts, Venn diagrams, layer stacks, pyramids, radar charts, loops, IT current-state maps, and more—all as static HTML+SVG that can be opened directly in a browser. The skill supports semantic patterns for behavior (queue, policy trace, trust boundary) and can convert existing draw.io/Mermaid sources, making it suitable for documentation, technical blog posts, internal wikis, and client deliverables. The ceiling includes fully customized, brand-aligned diagrams with optional motion for ordered explanations, all without external dependencies.

Bottom Line

This is ideal for technical writers, developers, and consultants who need polished, brand-consistent diagrams quickly and dislike the default AI-generated look. It's less suited for those who require complex, interactive diagrams or who prefer to work in vector editing tools. The key trade-off is a fixed set of visual types (27) versus the flexibility of a full drawing tool, but the quality and speed are unmatched for editorial-style output.

Full AI Analysis