Reading glossary

Paywall

A paywall is an access control a publisher places between a reader and an article, requiring payment, a subscription, or an account before the full text is available. Paywalls differ mainly in where they are enforced: in the browser after the page loads, or on the server before the article is ever sent.

Soft paywall

A soft paywall is a paywall enforced in the browser after the article has already been delivered. The full text is present in the page source, then hidden by an overlay, a height-limited container, or a script that strips paragraphs once a free-article counter is exceeded.

Hard paywall

A hard paywall is a paywall enforced on the server, where the article body is never sent to an unauthenticated reader. The response contains only a headline, a short excerpt, and a subscribe prompt, so no browser, extension, or proxy can recover the missing text.

Metered paywall

A metered paywall allows a set number of free articles in a period — commonly three to ten per month — and gates everything after that. The count is tracked in browser storage or against a signed-in account, and resets when the period rolls over.

Registration wall

A registration wall withholds an article until the reader creates an account or supplies an email address. No payment is involved: the publisher is trading access for a contact record and a signed-in session it can measure.

Cookie wall

A cookie wall conditions access to a page on accepting tracking cookies, often offering a paid, ad-free alternative. Common on European news sites, it is sometimes called consent-or-pay because refusing consent leaves only the subscription path.

Reader mode

Reader mode is a display mode that strips a web page down to its article — headline, byline, and body text — and re-renders it in a single readable column with controllable type, width, and theme. Navigation, sidebars, ads, and related-story modules are removed.

Article extraction

Article extraction is the process of turning a raw HTML page into a structured article — title, author, publication date, and body text — while discarding navigation, advertising, comments, and related-story modules. It is the step every reader mode, summarizer, and archive depends on.

Readability algorithm

A readability algorithm identifies the main article inside an HTML page by scoring elements on text density, paragraph length, link ratio, and class or id hints, then keeping the highest-scoring subtree. The Arc90 Readability approach and Mozilla's Readability.js are the reference implementations behind most reading views.

Distraction-free reading

Distraction-free reading is an approach to presenting text that removes competing elements — ads, autoplay video, newsletter prompts, social modules, notifications — so attention stays on a single column of content. The reader controls type size, line width, and theme instead of the publisher.

Read-it-later

Read-it-later describes saving an article at the moment it is found and reading it later from a personal queue rather than from the original page. The saved copy is typically stored as clean text, so it stays readable offline and survives layout changes on the source site.

Text fragment

A text fragment is a URL suffix in the form #:~:text=quoted%20words that tells a browser to scroll to a specific passage on a page and highlight it. It links to a sentence rather than to a page or a manually placed anchor.

AI summary

An AI summary is a shortened account of a source text produced by a language model. Extractive summaries reuse sentences from the original; abstractive summaries — what modern models produce — rewrite the material in new words, which is more readable and also where factual drift can enter.

Text to speech

Text to speech converts written text into spoken audio using a synthetic voice. Modern neural systems generate speech with natural prosody, and can stream audio as it is produced so playback starts before the whole text has been processed.

Video transcript

A video transcript is the text of what is spoken in a video, usually with timestamps that map each line back to a moment in the recording. Transcripts may be uploaded by the creator or generated automatically by speech recognition, which is faster but less accurate on names and jargon.

llms.txt

llms.txt is a plain Markdown file published at a site's root that gives language models a curated map of that site: what it is, which documents are canonical, and where to find them. Proposed in 2024, it complements robots.txt, which governs crawling rather than comprehension.

Model Context Protocol

The Model Context Protocol (MCP) is an open standard for connecting AI applications to external tools and data. A service implements an MCP server exposing tools and resources; any compatible client can then discover and call them without a bespoke integration on either side.