What turned up in the last three days — collected by machine, published by hand.
What gets picked here ends up in Teardowns →
Collected 2026-09-08 23:01 UTC · 46 kept from 280
2.2k stars67 forks
Apache-2.0TypeScriptpushed today
Location, estimated · Not stated
“Open-source AI brand visibility and competitor reports”
Published 2026-09-03
Fetched 2026-09-07 01:32 UTC · 138e30df9c592905
What the account wrote — The account left it blank
Torn from — the README
1.9k stars2.5k forks
AGPL-3.0Pythonpushed yesterday
Location, estimated · Elsewhere
“Local-first WeChat intelligence system with a read-only CLI, Codex skills, searchable chat history, daily briefings, follow-ups…”
Published 2026-09-04
Fetched 2026-09-06 23:01 UTC · 50d742bbbcd0f43f
What the account wrote — Canberra,Australia
Torn from — the README
1.1k stars180 forks
MITSwiftpushed today
Location, estimated · Not stated
“A macOS app that pins usage limits from Claude Code, Cursor, Codex, and Antigravity to a screen edge.”
Published 2026-09-05
Fetched 2026-09-06 23:01 UTC · 70a320489a90af6d
What the account wrote — The account left it blank
Torn from — the README
1.2k stars157 forks
MITPythonpushed yesterday
Location, estimated · Europe
“Free open-source project designed for turning youtube-viedos into viral short videos. Highlight detection, subtitles, translati…”
Published 2026-09-05
Fetched 2026-09-06 23:01 UTC · 06354c4b68f4ed99
What the account wrote — Paris
Torn from — the README
774 stars48 forks
Apache-2.0Pythonpushed today
Location, estimated · Not stated
“Continual learning infra for self-improving agents”
Published 2026-08-31
Fetched 2026-09-07 01:32 UTC · e535803553f886d7
What the account wrote — The account left it blank
Torn from — the README
655 stars54 forks
MITPythonpushed today
Location, estimated · Not stated
“DLSS 5 Neural Video & Image Enhancer with Frame Interpolation”
They claim — Frame Interpolation: single-video and batch-video processing with NVIDIA DLSS Frame Generation, selectable output rates from 23.976 to 480 FPS, and a three-second preview for a single sel…
Published 2026-08-30
Fetched 2026-09-07 01:32 UTC · 58b954054e451478
What the account wrote — The account left it blank
Torn from — the README
660 stars11 forks
MITShellpushed today
Location, estimated · Not stated
“Open-source SEO + GEO skills for Claude — keyword research, rank tracking, site audits, backlinks, competitor gaps, AI visibi…”
They claim — Look closer and most are a UI over the DataForSEO API: you either bring your own key and pay per request, or pay a hosted subscription plus a ~28% markup on every data call.
Published 2026-08-29
Fetched 2026-09-08 16:21 UTC · c7ee6c65bdba0676
What the account wrote — The account left it blank
Torn from — the README
612 stars35 forks
no licensePythonpushed today
Location, estimated · United States
This source gives a title and a link, nothing to quote.
They claim — Requires Python 3.12 or higher and uv.
Published 2026-09-01
Fetched 2026-09-08 16:21 UTC · 4719c1df68611e38
What the account wrote — United States of America
Torn from — the README
Nothing on this page matches what you picked.
Papers, repos, models, blogs, Reddit and podcasts — once a day, by machine. Everything collected gets taken apart once — the README, the abstract, the model card — and what that turns up is kept for good, whether or not it becomes a card. Titles and links go to the original; nothing is reproduced here.
The grey line on each card is what the teardown found, not what the source advertises: the licence, the last commit, the model it was built on, whether the paper states its own limits. Open “What we saw” to check what was read to get it. Where it says listing only, the original could not be read — some sites refuse us, and we do not pretend otherwise.
A line in quotation marks is a sentence lifted from the source itself — their number, not a measurement of ours. We copy it and leave it unchecked; that is the point of quoting it.
Topics are assigned by matching words in the original title, quote and tags against a fixed list — no model reads the card. Some cards match nothing and carry no topic at all; pick a topic and those drop out. Source and topic narrow together.
Each card keeps the sentence we actually read at the moment we read it, plus a fingerprint of the response we received. That sentence — not the whole page — is what we can still stand behind if the original later changes or disappears.
Guessed from one free-text field the account filled in itself, and half of them leave it empty. Shown as its own value rather than hidden.