# malevrigns/agent-jev > AgentJev-0.6B is a specialist decision model for AI agent loops: it takes unstructured state (diffs, traces, logs) plus typed questions and returns a probability distribution over options in a single forward pass with zero token decoding. - Magnitude: 5.4 out of 10 — Early signal - Stars: 137 total · +141 stars today, ≈ 190 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · License: Apache-2.0 · Created: 2026-09-21 · Last push: 2026-09-22 - GitHub: https://github.com/malevrigns/agent-jev · Page: https://gitnova.dev/en/r/malevrigns/agent-jev ## Useful for - Use it as a gate in an agent loop to decide whether tests passed without calling a large LLM - Pick the next tool from a set of options based on the current task state - Score whether a command is safe to run via a boolean question with a probability threshold ## Why it’s here - 141 stars so far today, about 190 expected by the end of the day. - The repository is 1 day old and already has 137 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #149. - About 32 forks a day — people are taking the code. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 6 - Issues and pull requests: 0 - Watchers: 0 - Average over the last week: 97 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 14 ## Stars per day, last 3 days (oldest → newest, today is partial) 2026-09-20 … 2026-09-22: 0, 3, 141 ## Spotted in now - Top new repositories this week: #149 ## Similar by description 1. **receptron/laya** — 5.5 · Early signal · Language models · TypeScript · +52 stars today, ≈ 89 by evening TypeScript wrapper for running the open-source Laya System-1 decision model via ONNX Runtime: takes a state and typed questions, returns answers with calibrated probabilities in one forward pass. Full card: https://gitnova.dev/en/r/receptron/laya.md 2. **kshetrajna12/reflex** — 2.4 · Early signal · Language models · Python · +6 stars today, ≈ 11 by evening An open decision model: given a state (text, JSON, or image) and typed questions, it returns calibrated probabilities over fixed answer options. Runs on top of Qwen3.5 and answers with numbers instead of free text. Full card: https://gitnova.dev/en/r/kshetrajna12/reflex.md 3. **NandhaKishorM/laya** — 9.2 · Breakout · AI agents · Python · +2,770 stars today, ≈ 4,520 by evening Laya is a non-autoregressive decision engine that answers typed questions (choice, score, noul) over any state (text, email, ticket, JSON) in a single forward pass (~35 ms on GPU) with calibrated probabilities. Full card: https://gitnova.dev/en/r/NandhaKishorM/laya.md 4. **Rizzo-AI-Academy/rizzo-flow** — 5.9 · Early signal · Language models · Python · +82 stars today, ≈ 140 by evening A local-first implementation of the Jev idea: an LLM returns typed decisions (boolean, choice, score, numeric) with probabilities in a single forward pass, without generating tokens. Compatible with the TypeSafe HTTP API. Full card: https://gitnova.dev/en/r/Rizzo-AI-Academy/rizzo-flow.md 5. **wdobry/laya-playground** — 4.7 · Early signal · Language models · JavaScript · +36 stars today, ≈ 55 by evening A playground for Laya, the open-source decision model: a website, three games, a benchmark and an agent skill. A local server takes typed questions and returns probabilities in one forward pass. Full card: https://gitnova.dev/en/r/wdobry/laya-playground.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-09-22 15:39 UTC, updated every 30 minutes.