The Unreasonable Effectiveness of ProseMirror Model in Rich Text Transformation
The article discusses the author's experience with ProseMirror, a rich text editing tool, and its application in their platform Storyteller. The author explains the challenges of synchronizing text and audio in ebooks, particularly due to limitations in EPUB file formats. They describe the need for unique identifiers in text spans to achieve accurate synchronization between written content and audio narration.
- ▪The author is a rich text editing engineer who uses ProseMirror extensively.
- ▪Storyteller is a platform designed to align ebooks with their audiobooks.
- ▪EPUB files present challenges for text-to-audio synchronization due to their markup limitations.
2 outlets in our directory ran this story. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
Lobsters files mainly under programming. We currently carry 187 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | smoores.dev |
| Canonical URL | https://smoores.dev/post/unreasonable_effectiveness_of_prosemirror/ |
| Publication time | Tue, 19 May 2026 06:52:27 -0500 |
| Retrieval time | 2026-05-19T12:04:57.562Z |
| Last seen | 2026-05-19T12:04:57.562Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 1KmhXjCQi49C · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
The Unreasonable Effectiveness of ProseMirror Model in Rich Text TransformationMay 18, 2026By day, I’m a simple rich text editing engineer. I spend almost all of my working hours thinking about, using, and sometimes reimplementing ProseMirror. I do love ProseMirror, probably quite a bit more than the next guy, but it is a little all consuming, if I’m being honest.Which is why by night I maintain Storyteller, a platform for automatically aligning, reading, and listening to readaloud-enabled ebooks. It has nothing at all to do with rich text editing, so obviously it doesn’t depend on ProseMirror.ObviouslyExcept about month a go I might have added a minimal implementation of ProseMirror Model in Storyteller’s alignment package.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at smoores.dev.