Read & learn
Written guides.
Understand Jev, one idea at a time. Walkthroughs, recipes, and writeups — our notes first, the original next.
A public registry · independent & community-run
Explore the Jev ecosystem.
Learn, build, and play with Jev — from deep technical guides to creative experiments.
Watch & learn
Video guides.
See an idea take shape. Tutorials, demos, and deep dives, organized by topic and credited to their creators.
Make & explore
Experiments.
See what builders made with Jev. Games, tools, repositories, articles, and more — traced to their sources.
The directory03 / 03 · Experiments
Find something worth exploring.
Every category, from games and tools to repositories and writeups, traced to a primary source.
Same 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.
1611 experiments · showing 481–540
Test whether Jev can choose compiler optimisation passes from program features, with its decisions compared against measured outcomes.
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A Pi extension masks stale tool output after Jev review while retaining paged access to the original session evidence.
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An Agent Skill and CLI convert decision prompts or calling code into validated Jev requests and runnable integration scripts.
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Review changed code for stylistic warning signs before it ships, with Jev mapping findings to a small verdict set.
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Filter MySQL rows with natural-language conditions through an AILIKE plugin backed by TypeSafe Jev.
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Run tool-using agents where Jev makes bounded decisions, deterministic code executes, and an LLM handles language when needed.
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JevGate reviews code, tests and documentation with small typed questions, then turns the answers into located findings.
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from the source
let first: Vec<_> = plan.requests.iter().map(Task::unit).collect();self.dispatch(report, first, |file, asked, body| { crate::units::record(file, &asked, body)})?;compose_files(&plan, report);
Paste JSON, a JWT, cron, stack trace, code, or prose and watch the page become the tool that content needs.
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An unofficial Ruby client for the TypeSafe AI API.
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from the source
client.system_one( state: { message: "I was charged twice." }, questions: { billing: { type: "noul", instructions: "Is this about billing?", weight: 2 }, tone: Typesafe::SDK::Choice.new(criteria: { calm: nil, angry: nil })
An idiomatic Java SDK for TypeSafe AI's Jev decision model.
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Use Zod schemas to check your data before asking Jev questions about it.
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from the source
import { z } from "zod";import { choice, noul, score, semantics } from "@mateonunez/jod";const Ticket = z.object({ message: z.string(), policy: z.string(),
An independent Rust SDK for the TypeSafe System One API with asynchronous and blocking clients.
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from the source
cargo add typesafe-ai-rs --git https://github.com/gilljon/typesafe-ai-rs --tag v0.1.0
An unofficial Java client for the TypeSafe System One API.
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A Neon Function proxy that routes TypeSafe Jev through the Neon AI Gateway.
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from the source
export SITE_URL="https://safer-with-jev.com"export API_URL="https://api.safer-with-jev.com"
A Jev-powered pull-request risk router and code-review coach.
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A Hermes plugin for typed decisions, ranking, verification, and optional tool gating with Jev.
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from the source
hermes config set plugins.entries.hermes-jev.settings.jev_model typesafe/jev-1.13 --forc...hermes config set plugins.entries.hermes-jev.settings.timeout_seconds 15 --force
A Python command-line agent that uses Jev while working through file-based questions.
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from the source
uv sync --group devcp .env.example .env# Fill in TYPESAFE_API_KEY and OPENAI_API_KEY in .env.uv run jevex 'Read prices.md. How much do three notebooks cost?' --trace run.jsonl
Give the Pi coding agent a way to ask Jev for decisions while it works.
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Slidepilot advances Slidev presentations by matching live speech to the next slide with Jev.
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from the source
pnpm installcp apps/worker/.dev.vars.example apps/worker/.dev.vars# Uncomment TYPESAFE_API_KEY in apps/worker/.dev.vars for real Jev inference.# Terminal 1pnpm dev:worker
Ask Jev questions from the command line, with answers as choices, scores or yes-or-no probabilities.
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from the source
typesafe info # endpoints; does not print the keytypesafe modelstypesafe smoke # docs quickstart exampletypesafe ask --state "…" --noul is_urgent="Does this convey urgency?"typesafe ask --state-file s.json --questions-file q.json --json
A Pi extension that checks risky tool calls and notices when a coding agent gets stuck.
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A browser harness where an LLM plans verifiable subgoals, Jev selects actions and fields, and Playwright executes them.
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from the source
npm start -- --goal 'register a user on example.com' \ --value 'name=Test User' \ --value 'email=user@example.com' \ --value 'password=a-test-password' \ --headed
A browser agent for Ego Lite that asks Jev or another agent to choose one action per observed page state.
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from the source
pnpm exec jev-ego serve --url https://en.wikipedia.org/wiki/Main_Page \ --goal 'Find and open the Wikipedia article about Gödel’s incompleteness theorems.'pnpm exec jev-ego observepnpm exec jev-ego suggestpnpm exec jev-ego act CLICK 4
An MCP browser agent that lets Jev choose each click and map supplied text values to form fields.
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from the source
claude mcp add jev-browse -e TYPESAFE_API_KEY=YOUR_API_KEY -- npx -y -p github:kyrylosyz...
In this browser stealth game, Jev judges the guards' actions while deterministic code runs the world.
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Jev flies a drone across a randomly generated city while avoiding obstacles between two points.
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Build and test Jev decision workflows in Python, then use them from the command line or an MCP client.
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choice
What is the tone? · calm / frustrated
A closer look at Jev 1.13.0, with controlled prompts and the raw answers available to inspect.
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jev-chat constructs chatbot replies by repeatedly turning Jev probabilities into hierarchical speculative decoding choices.
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from the source
git clone https://github.com/adhyaay-karnwal/jev-chatcd jev-chatuv sync --extra devcp .env.example .env # set TYPESAFE_API_KEY
Can Jev find better agent skills than embedding search? This evaluation tests both on Chinese and English queries.
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from the source
uv venv --python 3.12 .venv && uv pip install --python .venv/bin/python -e ".[dev]".venv/bin/pytest -q # 28 tests.venv/bin/python -m jse robustness # re-scores cached runs, no API key...export OPENROUTER_API_KEY=... # env only; never written to disk.venv/bin/python -m jse pool # ~30 min first time (bge-m3 over 3...
jev_stock experiments with short-term market-direction forecasts derived from structured financial data.
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This open-weights Jev alternative returns typed, calibrated choices in one Hugging Face or vLLM forward pass.
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from the source
pip install open-alternative-jev # Hugging Face backendpip install "open-alternative-jev[vllm]" # + vLLM backendpip install "open-alternative-jev[quant]" # + bitsandbytes 8-bit / 4-bit loading
Sort through training data with a Rust tool that asks Jev to score rows and filter out unwanted examples.
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A text-only Jev agent navigates Pokémon Red by turning parallel yes-or-no judgments into emulator button presses.
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A browser piano played by Jev, with your chosen mood guiding the performance.
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Watch Jev battle Pokémon in Showdown or FireRed by selecting one legal move or party switch each turn.
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Play chess or Connect Four against Jev, or spectate both sides while every legal move's probability remains visible.
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Let Hermes plan milestones while Jev chooses immediate actions for a Mineflayer bot in Minecraft.
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Watch a ViZDoom agent move at game speed while Jev periodically chooses its goal, target, direction, aim, jumps, and shots.
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Mark likely sponsor reads on a YouTube seek bar and skip them automatically using judgments made from captions.
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Paper-trade live markets with agents that ask Jev once a second whether prices look ready to rise, fall, or stay flat.
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Watch a U.S. equities dashboard combine fixed entry rules with Jev’s five-second review of market direction and risk.
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Edit a Mermaid support-routing flow, submit a ticket, and watch Jev’s answers illuminate the route it takes.
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A chat assistant for Feishu and WeCom that uses Jev to separate tasks and urgent requests from everyday chatter.
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Watch posts suspected of AI writing turn red or fold away on X, LinkedIn, and Reddit as you scroll.
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Give a browser one goal and watch Jev choose the next operation and indexed page element at every step.
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Mark or collapse X replies that resemble generic AI-written paraphrases of the original post.
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Split source code mechanically, ask Jev what each fragment is, and render the guesses as syntax highlighting.
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Sort loaded social comments into malicious, low-value, inspiring, or ordinary views while surfacing uncertain cases.
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Drop a folder of résumés into a desktop app and compare judgments of role, seniority, technical depth, and possible inflation.
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Compare Jev with another judge in a blind arena of bounded answer choices, then reveal the models after voting.
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Grade a page separately for search engines, answer engines, and generative-engine citation, then rank evidence-backed fixes.
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Search a Neovim buffer by describing behavior, then see matching functions ranked in quickfix and beside the code.
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Turns a straightforward request into an MCP tool call by choosing a discovered tool and filling simple arguments.
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Give an Android device a goal and let Jev navigate its accessibility tree one tap, swipe or back action at a time.
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Checks completed Pi replies for clarity and sends only the difficult ones to the configured model for a rewrite.
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Search source files, documentation and logs by describing the idea you need rather than its exact wording.
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An experimental OpenTelemetry processor that judges metric metadata before local policy annotates, reduces or drops instruments.
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Predicts which tests are safe to skip for a Git change, then runs the retained set through the existing framework.
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Plays Clash Royale on a real Android device by choosing a strategy, card and legal square from live screen perception.
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from the source
from typesafe_sdk import Choicecriteria = { strategy.name: {"what": strategy.meaning, "not_for": strategy.not_for}}
Jev, briefly
A decision model, not a chatbot.
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.
choice Pick one of these.
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.
score Rate this on a rubric.
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.
noul Is this statement true?
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
Patterns that keep showing up.
One decision per tick
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.
Confidence as a gate
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.
Shrink the choice space in code
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.
Jev judges, LLMs talk
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.
Made something with Jev?
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.
Submit your experiment → hello@JevMade.com