Read & learn
Written guides.
Understand Jev, one idea at a time. Walkthroughs, recipes, and writeups — our notes first, the original next.
Learn, build, and play with Jev — from deep technical guides to creative experiments.
Read & learn
Understand Jev, one idea at a time. Walkthroughs, recipes, and writeups — our notes first, the original next.
Watch & learn
See an idea take shape. Tutorials, demos, and deep dives, organized by topic and credited to their creators.
Make & explore
See what builders made with Jev. Games, tools, repositories, articles, and more — traced to their sources.

Every category, from games and tools to repositories and writeups, traced to a primary source.
Real-time research powered bySame ideas.
Different paths.
This is the full registry, not just the featured picks. Figures like speed, cost, and stars are maker-reported or captured snapshots, not JevMade measurements.
2140 experiments · showing 601–660
A Rust SDK for the TypeSafe AI API with bounded retry behavior.
An unofficial Laravel integration for Jev with typed responses and asynchronous requests.
Use Jev to rank search results and route requests in LlamaIndex.
Ailerix uses Jev to route each request to a model from a typed catalog.
A Codex plugin that uses Jev to restore verbatim context after session compaction.
A local proxy that uses Jev to choose the Claude model and reasoning effort for each message.
An agent skill that sends closed coding decisions to Jev for judgment.
An MCP server that exposes Jev tools for classification, scoring, checks, and batched questions.
Put a Jev check between an agent and its MCP tools to screen for unsafe calls and results.
A Claude Code hook that scores installed skills against the current task and hides irrelevant ones from the manifest.
An architecture skill for turning fuzzy semantic decisions into small Jev Choice, Score, or Noul questions.
A local workbench for building and publishing versioned Jev judgment functions.
An omp extension that uses Jev scores to reduce context while preserving selected passages verbatim.
A Pi extension that checks side-effecting tool calls against the user's stated constraints before they run.
Skill Router uses Jev to match a Claude Code session's goal with relevant installed skills.
A model router that uses Jev and a YAML policy to choose the least expensive LLM suited to each request.
A Jev-powered task classifier that routes work across three tiers.
A CI reviewer that uses Jev to assess the safety of database migrations.
A Claude Code mod that ranks installed skills for each prompt and answers the agent's binary questions when confidence is high.
A LiteLLM router that asks Jev to pick a model for each request.
A Chrome extension that uses Jev to navigate websites while guarding irreversible clicks.
A Go command-line tool that uses Jev to control macOS applications.
Browser automation with Jev choosing what to click and Playwright doing the clicking.
A frontend testing project built on Jev Ultrafast and Browser Harness, with evidence capture and a synthetic todo demo.
A privacy-focused Chrome extension that uses Jev to identify native ads, sponsored feed cards, and video ads.
A code-search CLI that asks the same yes-or-no question of every function and ranks the answers.
A small, dependency-free Python CLI for Jev Choice, Score, and Noul questions.
A TypeScript library that recursively navigates a taxonomy so Jev can choose among more than 255 options.
A live tone labeler for Bluesky posts and drafts using Jev.
A SQLite extension for filtering, ranking, classifying, and scoring rows with natural-language predicates evaluated by Jev.
A macOS window switcher that uses Jev to predict which window the user wants next.
A terminal interface pairs OpenAI answers with Jev routing, clarification and uncertainty decisions.
Every ten minutes, Jev revisits an absurd existential verdict using the day's strange news.
A playground gathers 110 editable Jev examples, from practical use cases to games and dilemmas.
Describe a use case and Jev selects the ingredients for a user interface without generating code or copy.
Calibre measures which model suits each part of a dataset, then routes requests using those results.
Test Jev on chess puzzles and on figuring out which game character you're talking to.
Eight small examples apply Jev to mechanical and electrical engineering decisions.
jev-gate experiments with assigning Claude Code tasks to different models according to Jev's judgment.
jev-harness adds confidence gates, shadow runs, reusable recipes, and evaluations around Jev decisions.
jevgpt coaxes a non-generative decision model into chatting by choosing the response one step at a time.
trade-jev backtests Jev as a buy, sell, or hold trader on Nasdaq futures order-book data.
jevify helps agents spot suitable Jev tasks, frame typed questions, and draw on recent community experiments.
A simulated Franka arm tries to stack a blue cube on a red one through a sequence of Jev-selected actions.
Set 22 Jev-controlled footballers loose on a 3D pitch, then inspect or take over any player.
Pit Jev's seven-move fighter against a simulated fly connectome and compare several live and offline control strategies.
Spectate two Jev-controlled Snake games side by side as each agent clicks only safe on-screen direction buttons.
An isometric world where Jev chooses actions for people with their own memories and limited knowledge.
A local browser runner reads a chess.com bot board, asks Jev for a legal move, and clicks it on the page.
Play chess against Jev or Stockfish, or let the two models play each other.
A collection of Jev demos led by a chess match presented like a TV broadcast.
A custom object detector helps Jev steer a watering can through Lazada's raindrop game on an attached Android device.
Speak through your notes while Jev quietly checks off each talking point once you have covered it.
Turn NYC 311 complaint text into explorable maps of reporting volume and Jev-estimated impact.
Guess whether a de-branded service belongs to AWS, Azure, or Google Cloud, then compare your answer with Jev’s probabilities.
Sweep through a synthetic inbox as Jev sorts messages, flags required action, and identifies mail that looks safe to trash.
Judge whether an article or video merits a read, skim, save, or skip before you open it.
Press a macOS shortcut, speak a command, and let Jev route it to a bounded app, typing, volume, or interface action.
Type beside a WebMCP-enabled page and watch Jev predict a schema-valid tool call as your request takes shape.
Type a short phrase and browse a many-emoji reply assembled from Jev's relevance scores.
Jev, briefly
A chat model generates text token by token and hopes you parse it. Jev never generates a word. Your code sends the state of the world plus typed questions; Jev returns every answer in one parallel pass — typed values with calibrated probabilities and a confidence score your code can trust. About 70–500 ms end to end, $0.042 per million input tokens, output free. Trained with what TypeSafe calls Reinforcement Learning for Calibrated Decisions.
You define the options. Jev returns the chosen option, a probability for every option, and a confidence. The workhorse of routing, agents, and games — the answer space is always legal, so there is nothing to parse and nothing to hallucinate.
You describe ordered levels — say trivial / normal / critical. Jev returns the level, the probability of each, and a confidence. Scores turn fuzzy judgment (“how severe is this log line?”) into a number-free decision your code can branch on.
You assert a statement; Jev returns the probability that it is true — a noul. Moderation, verification, guardrails, “does this diff actually fix the bug?”: one question, one calibrated probability.
Official material lives at typesafe.ai and docs.typesafe.ai. JevMade is an independent community registry — not affiliated with or endorsed by TypeSafe AI.
Recurring lessons
Games, drones, trading bots, and browser agents all converge on the same loop: serialize the state, ask one decisive question, act, repeat. Jev’s latency makes the loop feel instant — the model lives inside the control loop, not outside it.
The answer says what; the confidence says whether to act. The most reliable entries threshold on confidence to route edge cases to a slower model or a human — automation with an honest escape hatch.
Makers rarely ask Jev to pick from everything. Local tactics prune 225 gomoku moves to ~40; DOM filters turn a page into an element table; code narrows options, Jev judges within them.
A recurring split: Jev makes every decision cheaply and instantly, and a small LLM is only invoked when a human-facing string must actually be written. Decision and generation are separate budgets.
Send the link — repo, live demo, post, or video — plus a line on what it does and which primitives it uses. Every entry is verified against its primary source before it ships.
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