Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to addonscript.net

GitHub - Anvilcraft/addonscript-java: Moved to https://data.tilera.xyz/git/Anvilcraft/addonscript-java · GitHub · ranked by shared content topics & relevance
63match
piasek.dev
PiasekDev (Maciej Piasecki) · GitHub
2 shared topicstechnology-and-computing
63match
arpankotecha.dev
arpankotecha (Arpan Kotecha) · GitHub
2 shared topicstechnology-and-computing
63match
ariesmcrae.com
ariesmcrae’s gists · GitHub
2 shared topicstechnology-and-computing
62match
dmpayton.com
dmpayton (Derek Payton) · GitHub
2 shared topicsprogramming-languages
62match
1lubo.dev
1lubo — Java · Rust · Bitcoin · Nostr
2 shared topicstechnology-and-computing
62match
rodriados.com
rodriados (Rodrigo Siqueira) · GitHub
2 shared topicstechnology-and-computing
62match
mattiafochesato.com
MattiaFochesato (Mattia Fochesato) · GitHub
2 shared topicstechnology-and-computing
62match
gss-technology.com
CodeCrafters - Premium Developer Resources
2 shared topicstechnology-and-computing
61match
iodocs.com
A hub for all things related to development - iodocs
2 shared topicstechnology-and-computing
61match
piplotter.com
PiPlotter | PiPlotter and other project descriptions, tutorials, materials.
2 shared topicsprogramming-languages
61match
acrispycookie.dev
ACrispyCookie | Minecraft plugin developer
2 shared topicstechnology-and-computing
61match
code-sample.com
Anil Singh | Code-sample.com
2 shared topicsprogramming-languages
61match
piergiorgioyankah.com
Portfolio - To cook or to be cooked, that is the question.
2 shared topicstechnology-and-computing
61match
code-after-coffee.com
Hello from Code After Coffee Wiki | Code After Coffee Wiki
2 shared topicstechnology-and-computing
61match
arnavgosain.com
Arnav Gosain
2 shared topicsprogramming-languages
61match
docsharepro.com
Daan Meijers
2 shared topicsprogramming-languages
61match
gregbak.com
Greg Bąk — Senior Software Engineer
2 shared topicstechnology-and-computing
61match
nextfive.io
NextFive | Meetup
2 shared topicstechnology-and-computing

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.