libnyx

LT2MD

AI-agent skill producing reusable Markdown from PDFs. It turns flowcharts, diagrams, and charts into text beside each caption instead of empty links. It checks an earlier conversion against the PDF and fixes misread or missing parts. Long PDFs run in small saved batches with an independent review pass, each paragraph tagged with its page.

Community Project Python
114 stars via github-search
View on GitHub

Growth we measured

9 daily star snapshots stored by whatstrending.ai, 2026-09-04 to 2026-09-12. GitHub shows today's number; this is the movement behind it.

114111
2026-09-04 — 111 stars2026-09-05 — 111 stars2026-09-06 — 114 stars2026-09-07 — 114 stars2026-09-08 — 114 stars2026-09-09 — 114 stars2026-09-10 — 114 stars2026-09-11 — 114 stars2026-09-12 — 114 stars
2026-09-049 stored snapshots2026-09-12
Stars114our snapshot on 2026-09-12
7-day pace+0.4/day+3 stars · 2026-09-05 → 2026-09-12 (7 days)
30-day paceno data yettracked for 8 days so far
Trajectorynot enough historyneeds a short and a long measured window
First recorded2026-09-049 snapshots across 8 days

How this is measured. whatstrending.ai stores its own daily star and fork snapshot for every repo in its trending index. Every figure above is a delta between two of those stored rows — 9 snapshots for libnyx/LT2MD between 2026-09-04 and 2026-09-12. Our history starts 2026-06-19; we hold nothing from before that date. Nothing here is estimated, interpolated or back-filled, and days without a snapshot are simply not plotted.

For the maintainer

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libnyx/LT2MD is in the whatstrending.ai tracked index, so this badge already resolves. It is free, needs no account, and updates itself: the rank is recomputed from our stored daily snapshots and the image is re-fetched a few times a day. Clicking it lands on this page, which shows the star history we measured.

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