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The whole thread, not LinkedIn's sample. One click loads every comment on the post you're viewing, as clean text for your AI. Riff loads every comment and reply on a LinkedIn post and turns the thread into clean text you can hand to Claude, ChatGPT or Gemini. You ask the question. Riff only reads: it never posts, likes or comments. Why it matters Copy a busy LinkedIn post into an AI and it gets a fraction of the thread. In one test, a post with 60 comments reached Claude as 4 comments, plus buttons, reaction counts and sidebar text. Whatever the AI tells you is based on that sample. How it works 1. Open a LinkedIn post, on its own page or in your feed. 2. Click the Riff icon. 3. Click "Get post + every comment". Riff expands the thread for you, which can take up to 15 seconds. 4. Pick Claude, ChatGPT, Gemini or Clipboard only, then click Send. 5. The AI tab opens with the thread already in the message box. Add your question and press Enter. Questions to try - What objections keep coming up? - Who disagrees with the post, and why? - Which comments come from people who have done this themselves? What you get - Post author, headline and the full post text, including the "see more" part - Every comment and nested reply, with names, headlines and timestamps - A comment count, so you can see how much of the thread loaded - Copy as text or as JSON Privacy - No data collection. Everything runs in your browser. - No analytics, no tracking, no servers. - The text goes only to your clipboard or to the AI tab you choose. - Open source: https://github.com/mshadmanrahman/riff Built for founders, researchers and anyone who reads LinkedIn threads as evidence.
Nov 1, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.