Jev Wrapped
reads up to 1,500 posts from the last year of a public Telegram channel and asks Jev a `Choice` over ten kinds of post plus three `Noul` questions (paid ad, clickbait, emotional pressure) about each, counting an ad from 0.7, or from 0.4 when the kind is also ad, and clickbait and pressure from 0.5, then draws the monthly mix on a shareable card that links the highest-scoring posts for a manual check.
OWNER
gaborishka
INDUSTRY
Media analysis
CATEGORY
Classification & Routing
KIND
REPO
HOST
github.com
WHAT IT DECIDES
CHOICE
Picks one option from a fixed set
SCORE
Rates against ordered levels
NOUL
Answers a yes / no question
Inferred from this project's own one-line summary in the community list — it reads as a SCORE + NOUL decision. Read the source to confirm.
THE SHAPE OF A SCORE CALL
A generic skeleton for this question type, not this project's actual code.
from typesafe import TypeSafe
ts = TypeSafe()
result = ts.evaluate(
state=candidate,
questions={
"relevance": {
"type": "score",
"levels": ["low", "medium", "high"],
"instructions": "How relevant is this to the query?",
}
},
)
if result["relevance"] >= 0.7:
keep(candidate)MORE IN Classification & Routing
Notraproduction GEO platform whose `NOTRA_JEV_CLASSIFIERS` flag routes brand-visibility classifiers off an LLM and onto Jev `Boolean` decisions at a 0.5 threshold, targeting 300 ms p50.jev-routerroutes Claude Code tasks to the cheapest capable model by asking Jev to choose among candidates.jev-router (prismhq)open-source LiteLLM-based router where a Jev decision picks which model serves each request.pi-jev-routeradds automatic per-request model routing to the Pi coding agent through Jev decisions on Vercel AI Gateway.