#snarks
Live, measured metrics for the hashtag #snarks from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #snarks
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mas.to (Mastodon public tags API) · fetched 2026-11-12 09:00 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mas.to (Mastodon public search API) · fetched 2026-11-12 09:00 UTCLive pulse
measured · mas.to (Mastodon tag timeline) · fetched 2026-11-12 09:00 UTCEverything below is measured over the latest 14 public posts (spanning ~31891 hours).
Posting hours (UTC) — busiest: 10:00
Languages: English (13) · French (1)
Avg boosts / post: 0.1
Top of the latest posts
I finally read the recent Mercury paper. Like all papers by Ariel Gabizon it's very well-written. It makes Mercury a great introduction to the niche field of *Multilinear Polynomial Commitment Scheme*. Multilinear Polynomial Commitment Sche
Marius Van Der Wijden claims to have broken Iden3's implementation of the Poseidon Hash. It is quite well-known, and probably used, so it's quite interesting. He claims the problem is with their bit padding. Normally you add '1' and then ze
.... and done! A new CLI tool for creating Merkle trees using the #Aztec implementation of Pedersen hash. It's one of those things you build because you need it yourself. It's super niche obviously, but if you're using #noir or into #snarks
What “snarks” means
Wiktionarysnarks
- nounA graph in which every node has three branches, and the edges cannot be coloured in fewer than four colours without two edges of the same colour meeting at a point.
#snarks across platforms
every network with a public tag surfaceFollow #snarks straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/snarks