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Rich Text

A semantic Value Type storing formatted markdown content, signalling the UI to mount a block editor.

type: data-model · status: draft · abstraction: instance

What it is​

A Rich Text property stores content that requires semantic formatting — such as headers, lists, emphasis, and hyperlinks. Under the hood, this data is persisted as standard Markdown. This ensures maximum portability, easy consumption by AI agents, and straightforward integration with external tools via the API.

When the IMOS client encounters a Rich Text value type on a Record, it automatically mounts a full rich text or block-based editor rather than a standard text area. This allows workflows to mix highly structured quantitative data (like Measurements and Money) with long-form qualitative documentation, all on the same Record.

Why it exists​

While standard primitive strings are sufficient for simple fields like a part name or a short tracking note, complex manufacturing workflows frequently deal in documents. Engineering change orders, non-conformance resolutions, and assembly instructions all require structured, readable text.

By defining Rich Text as a distinct value type backed by Markdown, we guarantee a superb human editing experience on the frontend whilst keeping the underlying data clean and predictably formatted for the AI agents that will inevitably read or generate it.

Relationships​

Outgoing

  • is an instance of → Value Type (many-to-one)
  • references → Asset (one-to-many) — Rich Text remains Markdown on the Record and may contain internal references to Assets.

Neighbourhood​

Stakeholder summaries​

  • Product — Provides a first-class block editor for long-form fields like non-conformance reports, standard operating procedures, and meeting notes.
  • Investor — Captures unstructured institutional knowledge in a high-fidelity format, significantly increasing the value of the proprietary dataset we can feed into AI workflows.
  • Marketing — Gives users a beautiful, modern document editing experience right on their manufacturing records, removing the need to jump out to Word or Notion.
  • Engineering — Stored natively as raw Markdown strings, ensuring lightweight persistence and native compatibility with LLM input/output.