# Scoring & Ranking

Use this category for programs where Jev produces rubric scores, quality grades, or relevance and priority orderings that drive a downstream decision.

## Submission format

```md
- [Name](URL) - Industry: one-sentence description of the Jev use case.
```

## Entries

- [Clean Code Judge](https://github.com/frostney/clean-code-review) - Code quality: scores every file of a pull request on 31 boolean Clean Code smells plus function size and nesting, then hands the verdicts to a writing model for the review prose.
- [citation-verifier](https://github.com/MarissaFamularo/citation-verifier) - Academic publishing: checks whether each cited paper actually supports the sentence citing it, with Claude locating the quote, Jev scoring the support, and a human making the final call.
- [jev-assist](https://github.com/glud123/jev-assist) - Coding agents: ranks every tracked file by relevance to a one-line task description — Jev asks each file the same typed question in parallel batches, so an agent in a 600-file repo starts from the handful it actually needs — with a validate command that grades the ranking against past commits.
- [jev-ai-detector](https://github.com/igloomatics/jev-ai-detector) `{type: extension}` - Writing analysis: Chrome extension which gives readers an instant, uncertainty-aware signal for how strongly selected webpage text resembles AI-generated writing, using Jev inline in Chrome without interrupting reading.
- [jev-bfs](https://github.com/komikat/jev-bfs) - Search tooling: finds link paths between English Wikipedia articles by having Jev rank each page's outgoing links while Python controls the search.
- [Jev Search](https://github.com/superagents-lab/jev-search) - Web search: uses Jev Noul judgments on result titles and snippets to rank Search1API results by relevance, with application code merging duplicate URLs and grouping lower-scoring matches separately.
- [Tweet Radar](https://github.com/kelaocai/tweet-radar) - Social reading: uses Jev `Noul` to score already-loaded X posts against a reader's goal and profile, then pairwise `Choice` judgments to rank eligible matches and surface up to three for review.
- [pagegrade](https://github.com/kitze/pagegrade) - Content quality: grades page sections for clarity, writing, and on-page SEO with Jev and returns per-section scores.
- [jev-scout](https://github.com/AkashPriyadarshii/jev-scout) - Developer tooling: sub-second zero-hallucination open-source repo and crate scout using TypeSafe Jev speculative fan-out scoring.
- [jev-seo](https://github.com/AkashPriyadarshii/jev-seo) - Zero-cost, agent-first SEO & Generative Engine Optimization (GEO) search radar CLI suite and MCP server powered by DuckDuckGo and TypeSafe Jev System One.
- [JevSlop](https://github.com/TKY-27/JevSlop) - Writing quality: scores public note.com articles on eight Jev `Score` axes inside a single `systemOne` request and turns them into a 0-100 Slop Score in ordinary TypeScript.
- [Supercov](https://github.com/supercorp-ai/supercov) - Code quality for coding agents: Jev answers twelve `Noul` properties per source file so the agent knows what to fix first.
- [jev.nvim](https://github.com/valentynkit/jev.nvim) - Developer tooling: Neovim plugin that splits the buffer into functions with Treesitter, scores each against a plain-language question with Jev, and ranks answers by probability in quickfix.
- [jev-reranker](https://github.com/hotchpotch/jev-reranker) - Retrieval and RAG: uses Jev Noul judgments to assess retrieved documents for relevance and usefulness as answer evidence, then sorts results and optionally filters them using a configurable threshold.
- [Jev Reranker (Rust CLI)](https://github.com/shinpr/jev-reranker) - Retrieval and RAG: JSON-in/JSON-out CLI that uses separate Jev `Noul` checks to rank candidates, apply evidence thresholds, or extract source text while keeping those decisions independent.
- [jev-skip](https://github.com/valentynkit/jev-skip) `{type: extension}` - Media: browser extension that reads the YouTube caption track and scores each segment's sponsor probability on the seek bar before the intro ends, reporting 77% of SponsorBlock's sponsor seconds caught over 23 videos at $0.0008 a video.
- [jev-semgrep](https://github.com/uehaj/jev-semgrep) - Semantic search: greps by meaning across languages, having Jev score every line against a meaning and letting meanings combine with AND, backed by a 13-file test suite.
- [nlgrep](https://github.com/YehuiTang0316/jev-nlgrep) - Developer tooling: uses Jev `Noul` judgments to find code, docs, logs, and text satisfying natural-language conditions, with a configurable probability threshold and ranked file results linked to source lines.
- [JevPDF](https://github.com/kylemclaren/jevpdf) - Document search: in-browser PDF viewer that extracts each page's lines locally with pdf.js and asks Jev one `Noul` per line on whether it answers the query (16 lines per request, sharing the page text as state), highlighting lines at or above 0.55 page by page and ranking them by probability.
- [slop-grader](https://github.com/lukstei/slop-grader) - Content quality: CLI tool that grades text files against custom rulesets for AI slop, grammar, and technical doc quality using Jev scores and line-level flags, then guides an AI agent to auto-fix violations.
- [jselect](https://github.com/keltokhy/jselect) - Research and retrieval: selects source-linked evidence within a token budget using Jev Noul relevance judgments and local diversity-aware selection.
- [jsort](https://github.com/keltokhy/jsort) - Text measurement: ranks text along a plain-English criterion using pairwise Jev Noul comparisons and a locally fitted Bradley-Terry scale.
- [jgrep (kyu1204)](https://github.com/kyu1204/jgrep) - Developer tools: semantic grep that asks Jev one Noul per 5-60 line code chunk, diff hunk or CSV row (16 per request) and prints grep-style file:line hits above a threshold, so English sentences work as CI lint rules.
- [jev-resume-screening](https://github.com/nanami-0713/jev-resume-screening) - Recruiting: screens one resume against a JD in a single request of five Noul evidence gates, four Score dimensions, and one background-routing Choice, with criteria hardened v1→v3 against negative-control resumes (a glossy-trap CV's self-described "AI heavy user" fell 0.95→0.49) and any low-confidence answer escalated to human review.
- [hippo-memory](https://github.com/kitfunso/hippo-memory) - Agent memory: a biologically-inspired memory store whose optional Jev reranker lifts recall R@1 from 0.41 to 0.62 on a private 300-query developer store.
- [MemSearch Jev reranking](https://github.com/zilliztech/memsearch/blob/main/evaluation/reranking-evaluation.md) - Coding-agent memory: an optional Jev reranker asks Noul questions about retrieved Markdown chunks and sorts them by relevance to the query, with bilingual evaluation results.
- [Oko](https://github.com/bartlomein/oko) - Developer tooling: local code search for coding agents that shortlists function-level chunks with ripgrep and BM25, asks Jev a `Noul` relevance question per chunk across three parallel requests, and returns the accepted ones as excerpts through MCP; the cutoff and excerpt selection live in code.
- [grokbot-jev-jobs](https://github.com/mcgalleg/grokbot-jev-jobs) - Job search: a daily Vercel cron that scores public job postings against one resume with Jev through the Vercel AI Gateway, so only the plausible matches surface.
- [jeff](https://github.com/saembit/jeff-cli) `{type: cli}` - Developer tooling: Go CLI whose rank command asks one Jev `Score` per item per weighted dimension of a YAML spec in a single request and sums weight times score in code to order the items, with noul, choice and score commands that turn a threshold into exit code 10 for shell scripts and CI.
- [Paper Radar](https://github.com/Eliot5566/JEV-Paper-Radar) - Research: scores every new arXiv and bioRxiv paper against plain-English interests with one Noul each and publishes the top picks as a daily page and RSS feed.
- [Refix](https://refix.ai) - Growth: asks Jev a `Score` over each experiment result to decide whether it clears the promotion bar, and a `Choice` over candidate plays to decide what to run next in SEO, content, and ads.
- [OpenViking](https://github.com/volcengine/OpenViking) - Reranking: Volcengine's agent context database ships a Jev rerank client that scores each candidate document with `jev-latest` against `api.typesafe.ai` and treats the returned probability as relevance, because TypeSafe exposes no native rerank endpoint.
- [jevsearch](https://github.com/kylemclaren/jevsearch) - Site search: shadcn/ui command-palette block that streams keyword hits on the first keystroke, then sends the top 20 to Jev in one request (a `Noul` per page on whether the visitor would be glad to land there, a `Choice` for the single best answer, and a `Noul` on whether any page answers at all) and re-orders or drops hits in code, with the repo's own benchmark over the 109-page TypeSafe docs reporting Hit@1 of 83% against 41% for its keyword pass alone.
- [jev-retrieval](https://github.com/romeromarcelo/jev-retrieval) `{agent: claude-code, type: cli}` - Coding agents: Rust CLI (`jevr`) that turns a natural-language query into grep-style `path:start-end` targets — a stateless local BM25 pass proposes candidates, Jev `Noul` membership questions score their 100/20-line windows (kept at 0.90 for code, 0.60 for docs), and one listwise `Choice` per lane orders the keepers — ships as a Claude Code skill and plugin, and placed 2nd of 90 models on the HAKARI-Bench NanoRTEB reranking leaderboard.
- [Vector Graph RAG](https://github.com/zilliztech/vector-graph-rag) - Multi-hop retrieval: uses Jev Noul judgments to score candidate relations and applies a configurable threshold before retrieving their linked documents.