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Written guides.
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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 541–600
A terminal oracle that answers any question with a bare Yes or No, then renders the verdict in a 3D hyperspace.
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from the source
body: JSON.stringify({ state: question, model, questions: { [QUESTION_KEY]: {
Searches several web backends, then uses Jev to keep useful results, confirm duplicates and filter scraped page chunks.
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from the source
// NoulQuestion builds a yes/no question.func NoulQuestion(instructions string) Question { return Question{Type: TypeNoul, Instructions: instructions}}
Let jev-ra drive the browser for a coding agent: Jev picks the next action and the page element to use.
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Prunes DeepSeek Harness tool results according to Jev judgments while retaining deterministic context receipts.
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Turns a plain-language request into a macOS menu action by scoring every available menu path with Jev.
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Chooses a meal from a personal candidate pool by combining Jev suitability checks with a final bounded choice.
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Tests Jev and the open-weight Laya counterpart as typed judgment layers in a look-ahead-free quantitative research stack.
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Analyzes JSON, NDJSON, and JSONC windows with reusable typed question packs, preserving source-line anchors for every answer.
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Exposes Jev’s three decision types as one MCP tool for coding-agent routing, risk checks, and bounded architectural choices.
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Ask Jev typed questions from the command line, lint question sets before billing, and send machine-readable answers to scripts or agents.
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Add fail-closed input moderation to a Mastra agent with one Jev request and a typed tripwire instead of parsing a language-model verdict.
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Ask typed questions directly about images through a shared Qwen3-VL encoding instead of first producing captions.
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Let Jev choose destinations and battle actions while deterministic code reads Pokémon FireRed RAM and presses the controls.
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Load only the SKILL.md files a LangChain agent needs for its current turn, with Jev available as a judge.
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Route, score, or check n8n items with Jev, including parallel requests and multi-item batches.
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Build a personal Hacker News feed by scoring new stories and articles against interests saved by each reader.
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An Elixir SDK for unified LLM integrations, including Jev support.
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An unofficial Go SDK for TypeSafe AI with typed answers, retries, and context support.
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from the source
question := typesafe.Noul("is this time sensitive?")question.Criteria = &typesafe.NoulCriteria{ True: "an explicit deadline or immediate impact", False: "no time constraint is expressed",}
A Swift SDK for TypeSafe AI.
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A .NET SDK for the TypeSafe AI platform.
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A Scala client for TypeSafe AI built with ZIO.
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from the source
src/main/scala/com/jamesward/zio_typesafe_ai/ TypeSafeAI.scala — top-level object: Client, Content, Question, ChoiceCriteria, ScoreCriteria, NoulCriteria, Probability, ChoiceAnswer, ScoreAnswer, Result, Error, opaque ids, AnswerOf,
A Rust SDK for the TypeSafe AI API with bounded retry behavior.
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score
How urgent is this ticket?
An unofficial Laravel integration for Jev with typed responses and asynchronous requests.
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Use Jev to rank search results and route requests in LlamaIndex.
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Ailerix uses Jev to route each request to a model from a typed catalog.
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A Codex plugin that uses Jev to restore verbatim context after session compaction.
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from the source
npm installnpm run typecheck # librarynpm run check:hooks # node --check on every hook scriptnpm test # unit tests, fake Jev, no networknpm run build # emit dist/ (checked in: hooks import it)
A local proxy that uses Jev to choose the Claude model and reasoning effort for each message.
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from the source
Claude Code ---> jcm-router (localhost:8787) ---> api.anthropic.com | +---> api.typesafe.ai (Jev: "which model? how much effort?")
An agent skill that sends closed coding decisions to Jev for judgment.
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An MCP server that exposes Jev tools for classification, scoring, checks, and batched questions.
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Put a Jev check between an agent and its MCP tools to screen for unsafe calls and results.
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from the source
npx -y github:caiovicentino/jev-shield install-hooks # opt in: hook + plugin (merges...npx -y github:caiovicentino/jev-shield uninstall-hooks # opt out: removes hook + plugi...JEV_HOOK_OFF=1 # kill switch (env), JEV_FAIL_M...
A Claude Code hook that scores installed skills against the current task and hides irrelevant ones from the manifest.
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An architecture skill for turning fuzzy semantic decisions into small Jev Choice, Score, or Noul questions.
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from the source
# from this repocp -R skills/jev-system-architect ~/.cursor/skills/jev-system-architect# or wherever your agent loads skills from
A local workbench for building and publishing versioned Jev judgment functions.
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from the source
pip install typesafe-sdkexport TYPESAFE_BASE_URL=http://127.0.0.1:17420export TYPESAFE_API_KEY=$JEV_CLIENT_TOKEN
An omp extension that uses Jev scores to reduce context while preserving selected passages verbatim.
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from the source
grep "jev context" ~/.omp/logs/omp.$(date +%F).*.log | tail -3# jev context: 33906->27067 chars, dropped=5, asks=4, cacheHits=20
A Pi extension that checks side-effecting tool calls against the user's stated constraints before they run.
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Skill Router uses Jev to match a Claude Code session's goal with relevant installed skills.
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from the source
$ skill-router intent set "write the cold outreach sequence for our fintech prospects"[skill-router] Session goal: write the cold outreach sequence for our fintech prospectsJev: task kind `marketing_growth`, needs-a-skill 0.84.Relevant installed skills for this session: /cold-email (probability 1.00) — Write B2B cold emails and follow-up sequences that ge...
A model router that uses Jev and a YAML policy to choose the least expensive LLM suited to each request.
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from the source
request ─► Jev: 11 questions, one call, ~180 ms ─► your YAML policy ─► model, fallback,... difficulty · stakes · needs_reasoning thresholds on probabilities; safety · domain · output_length · ... context, capability, and budget...
A Jev-powered task classifier that routes work across three tiers.
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A CI reviewer that uses Jev to assess the safety of database migrations.
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from the source
sequenceDiagram autonumber actor Dev as Developer / Git Push participant CI as GitHub Actions Pipeline participant MG as Migration Guard API (/api/migration-guard)
A Claude Code mod that ranks installed skills for each prompt and answers the agent's binary questions when confidence is high.
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A LiteLLM router that asks Jev to pick a model for each request.
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from the source
pip install "litellm[proxy]" pyyamlexport OPENROUTER_API_KEY=sk-or-...# optional — enables Jev routing instead of the baselineexport TYPESAFE_API_KEY=...litellm --config config.yaml --port 4000
A Chrome extension that uses Jev to navigate websites while guarding irreversible clicks.
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A Go command-line tool that uses Jev to control macOS applications.
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from the source
computer-use-jev -goal 'in TextEdit, type "hello world"'computer-use-jev -goal 'open Safari and take a screenshot' -jsoncomputer-use-jev -goal '...' -dry-run # decide, don't actcomputer-use-jev -goal '...' -max-steps 24
Browser automation with Jev choosing what to click and Playwright doing the clicking.
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from the source
npx jev-browser open https://example.com --session worknpx jev-browser snapshot --session work# Use the ref returned by snapshot, or a caller-authored Playwright selector:npx jev-browser click 'a' --session worknpx jev-browser take_screenshot --args '{"filename":"page.png","fullPage":true}' --sessi...
A frontend testing project built on Jev Ultrafast and Browser Harness, with evidence capture and a synthetic todo demo.
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A privacy-focused Chrome extension that uses Jev to identify native ads, sponsored feed cards, and video ads.
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from the source
# Clone the repositorygit clone https://github.com/vmendes90/jev-shield.gitcd jev-shield# Install dependenciesnpm install
A code-search CLI that asks the same yes-or-no question of every function and ranks the answers.
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from the source
pip install every-cli # installs the `every` commandexport TYPESAFE_API_KEY=... # PowerShell: $env:TYPESAFE_API_KEY="..."every --selftest # 20 labelled functions, one request; prints recall / fa...
A small, dependency-free Python CLI for Jev Choice, Score, and Noul questions.
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choice
Which team should handle `message`?
A TypeScript library that recursively navigates a taxonomy so Jev can choose among more than 255 options.
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from the source
import { createJevTree } from 'jev-tree';const tree = createJevTree({ maxFanout: 32 });const result = await tree.select({ state: 'Replica lag 47m on primary still accepting writes', question: 'Which incident type is this?',
A live tone labeler for Bluesky posts and drafts using Jev.
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A SQLite extension for filtering, ranking, classifying, and scoring rows with natural-language predicates evaluated by Jev.
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A macOS window switcher that uses Jev to predict which window the user wants next.
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A terminal interface pairs OpenAI answers with Jev routing, clarification and uncertainty decisions.
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from the source
flowchart TD U[Human asks a question once] --> J1[TypeSafe Jev: routing decision] J1 --> D1[Choice: response mode] J1 --> D2[Noul: clarification required] J1 --> D3[Noul: uncertainty notice required]
Every ten minutes, Jev revisits an absurd existential verdict using the day's strange news.
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from the source
wrangler pages secret put TYPESAFE_API_KEYnpm run deploy
A playground gathers 110 editable Jev examples, from practical use cases to games and dilemmas.
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noul
Does the message ask for an unresolved action?
Describe a use case and Jev selects the ingredients for a user interface without generating code or copy.
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Calibre measures which model suits each part of a dataset, then routes requests using those results.
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Test Jev on chess puzzles and on figuring out which game character you're talking to.
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from the source
jevcommon/client.py rate-limited async TypeSafe client; persists every raw request/...jevchess/ chess benchmark state.py board → state at three levels (fen / ascii / rich); move descri... experiments.py A–G: Choice, Score fan-out, hierarchical, perception, mate-in-1... engine.py positions.py Stockfish ground truth; position generation
Eight small examples apply Jev to mechanical and electrical engineering decisions.
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jev-gate experiments with assigning Claude Code tasks to different models according to Jev's judgment.
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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