Event JSON
{
"id": "d9f7ace8d8b3c3939efa12ae27df7ad85c7200b3614a13bbf2e21fcc58eae3b0",
"pubkey": "f11538efcaf48bceb1750a17cb39068887aadd85fd88fe9603a486bb44a83dac",
"created_at": 1738913984,
"kind": 1,
"tags": [
[
"p",
"3591214212a5a60ca429e76746343ad3ab2901bcf86afdbf27851c0d117c7d23",
"wss://relay.mostr.pub"
],
[
"p",
"dda3e68a35429b62c761d775269b6bcf31977fd13db171c3d3ef32998ae006c1",
"wss://relay.mostr.pub"
],
[
"e",
"354f8c5425f94f538b15400c6fb4c2de77d8957a41e6333f8f88299a85ac1083",
"wss://relay.mostr.pub",
"reply"
],
[
"proxy",
"https://infosec.exchange/users/adp/statuses/113961466888187231",
"activitypub"
]
],
"content": "nostr:nprofile1qy2hwumn8ghj7un9d3shjtnddaehgu3wwp6kyqpqxkgjzssj5knqefpfuan5vdp66w4jjqdulp40m0e8s5wq6ytu053sz6e6vs I've been finding that it seems to make sense/ be similarish to the android/Google fit counting (which I also presume is generally an estimate) I've not compared to anything else much..",
"sig": "b78afbf478a02d896fc4c702ebdf624d8c3d96b0949bd05b3444ca648237987c94a2e89b038a578145c8a726774c899b1859a6d264c9f39b80bed482eaf10f03"
}
