Mermaid is a mature, browser-oriented TypeScript monorepo that renders Markdown-like text definitions into SVG diagrams. In production it supports over 20 diagram families (flowchart, sequence, class, state, gantt, mindmap, pie, git, ER, C4, sankey, block, agentflow, and more), with a pipeline that detects diagram type from text, lazily loads a parser, builds a diagram-specific data model, and renders through a shared rendering-util layer. Parsing is split across Langium, Chevrotain, and legacy JISON grammars; layout is provided by dagre, ELK, a custom swimlane/orthogonal router, and tidy-tree plugins. The public API (initialize/run/parse/registerExternalDiagrams) makes this a plugin-extensible library rather than a standalone application, though it also ships a local editor, dev-explorer, and extensive e2e tooling. The codebase shows high engineering craft: CI is extensive with Vitest, Playwright visual regression, code coverage, security scanning, dependency automation, and changesets for versioning. Accessibility, XSS sanitization, and config validation are treated as first-class concerns. The theme system is particularly well-structured, managing multiple looks and color palettes through a centralized color-theme gate. The primary weaknesses are scale-driven: mixed parser ecosystems, a very large config surface, many beta diagram types, and highly intricate layout code that is expensive to change. It is neither a data-research repository nor a service; its research-like components are the layout algorithms and geometry validation, which remain embedded in a library architecture.
drawio-skill is a comprehensive toolkit for generating, manipulating, validating, and publishing draw.io architecture diagrams from natural language, codebases, infrastructure-as-code, API specifications, and other structured sources. It provides a unified CLI (`diagramctl.py`) and an optional MCP server (`diagramctl_mcp.py`) that expose workflows for building, syncing, viewing, testing, reviewing, querying, what-if analysis, story generation, and publishing diagrams. The system uses a formal Diagram Intermediate Representation (IR) to separate semantic meaning from geometry, enabling incremental reconciliation, multi-view projection, architecture contract enforcement, and accessible HTML story output. It includes 15+ importers for languages (Python, JS, Go, Rust), IaC (Terraform, Kubernetes, Docker Compose), schemas (SQL, OpenAPI, AsyncAPI, Protobuf, GraphQL), and live infrastructure (Docker, Terraform state). The project is packaged as an AI agent skill compatible with Claude Code, Cursor, Copilot, and other Agent Skills hosts, and ships with GitHub Actions for CI integration. While primarily an application, it also bundles curated icon indices and style presets that could be considered data assets.