v-modal/awesome-jev-tools

awesome-jev-tools

A curated awesome list of public projects and practices built on Jev, TypeSafe AI's System One model for typed decisions.

This README is the homepage aggregate of the current category files, so the latest accepted entries are visible here without drilling into subpages.

A curated list of public projects and developer patterns built on Jev, TypeSafe AI's System One model for typed decisions.

What is Jev? Jev is not a chat model. It does not write text or hold conversations.

Instead, it takes unstructured state alongside a typed question and returns a typed decision—such as a choice, a score, or a boolean—accompanied by a confidence rating.By eliminating token-by token decoding, Jev acts as a fast, low-latency decision layer directly inside software.

Developers use it to handle classification, infrastructure routing, rubric scoring, verification gates, and autonomous agent guardrails.Goal of this ListMost discussions about Jev are scattered across launch threads, social media, and one-off prototypes.

This repository centralizes those pieces to answer two practical questions for developers:

• Production Validation: Where is Jev actively making real decisions in live production workflows?
• Transferable Patterns: Which decision architectures can be cleanly copied and applied across different industries?

Goal of this list

Most Jev discussion is scattered across launch threads, model-gateway listings, and one-off prototypes. This list answers two practical questions quickly:

• Where is Jev already making real decisions in production workflows?
• Which decision patterns transfer across industries?

Inclusion criteria

We do not include:

• Generic classifiers, routers, or research agents that merely resemble the pattern without using Jev.
• Pure theory or opinion without a concrete practice.
• Launch-hype commentary with no working artifact or reproducible result.
• Long write-ups inside the list itself.
• Sources that are private, inaccessible, or too vague to classify.

Curation is not endorsement

Inclusion means one thing: the entry satisfies the inclusion rules above. It is not a quality review, a security audit, or a recommendation. We do not verify that a project compiles, that its tests pass, that its published numbers reproduce, or that its license permits your use.

This matters most for projects that arrive in bulk. When one author releases several repositories on the same day, they commonly share a single scaffold — the same AGENTS.md, CLAUDE.md, STATE.md, and CHANGELOG.md — land in one or two commits each, and may ship considerably more prose than code. Such projects can be entirely legitimate; they are simply unproven. Treat them as leads, not as validated tools.

Before adopting an entry, check it yourself:

| Check | Why it matters | | --- | --- | | Does the code actually call the Jev API? | An entry can read well on a README alone. Look for a real request carrying typed questions, and a parsed answer coming back. | | Is there a runnable check? | A test, an example with expected output, or a public demo. No check means no evidence that it works. | | Do the numbers have a source? | Any accuracy, latency, cost, or volume figure should be traceable to the linked page. We strip claims we cannot verify, but the project page itself may still carry them. | | How much of the repository is code? | Some projects are mostly prompt documents. That can be legitimate — just know which one you are getting. | | Is there a license? | A few entries have none, which limits reuse and redistribution. |

Found something wrong? Open an issue or a pull request — removal is as valid a contribution as addition. Rules for AI-assisted work, project depth, and submission rate live in CONTRIBUTING.md.

Current coverage

• Classification & Routing — 20 entries
• Verification & Guardrails — 20 entries
• Scoring & Ranking — 13 entries
• Agent Decisions — 29 entries
• Data Labeling & Curation — 2 entries
• Evaluation & Benchmarking — 13 entries
• Calibration & Research — 17 entries
• Infra / SDKs / Integrations — 33 entries
• Game & Simulation — 8 entries
• Finance & Trading — 3 entries
• Compliance & Legal — 1 entry
• Content Moderation — 3 entries
• Related Practices / Discussions — 50 entries

Open categories still being seeded

• Scientific Pipelines — 0 entries

Each entry lives in exactly one category. When a project could fit multiple categories, we choose the one closest to its direct application domain.

Browse by category

• Classification & Routing (source)
• Verification & Guardrails (source)
• Scoring & Ranking (source)
• Agent Decisions (source)
• Data Labeling & Curation (source)
• Evaluation & Benchmarking (source)
• Calibration & Research (source)
• Infra / SDKs / Integrations (source)
• Game & Simulation (source)
• Finance & Trading (source)
• Compliance & Legal (source)
• Content Moderation (source)
• Related Practices / Discussions (source)

Full list

Classification & Routing

Source file: categories/classification-routing.md

• Notra - Marketing analytics: production GEO platform whose NOTRA_JEV_CLASSIFIERS flag routes brand-visibility classifiers off an LLM and onto Jev Boolean decisions at a 0.5 threshold, targeting 300 ms p50.
• jev-router - Developer tooling: routes Claude Code tasks to the cheapest capable model by asking Jev to choose among candidates.
• jev-router (prismhq) - LLM infrastructure: open-source LiteLLM-based router where a Jev decision picks which model serves each request.
• pi-jev-router - Coding agents: adds automatic per-request model routing to the Pi coding agent through Jev decisions on Vercel AI Gateway.
• jcm-router - Coding agents: local proxy that picks the Claude model and reasoning effort per message with a Jev decision while leaving the cached main chat untouched.
• jev-agent-skill-router - Agent infrastructure: routes agent skill selection through typed, confidence-aware Jev decisions so weak matches are declined instead of guessed.
• typesafe-jev CV screener - Recruiting: screens a folder of CVs with Jev typed judgments against an editable policy, re-scoring candidates for free when the policy changes.
• Jev email intent workflow - Back-office automation: async LangGraph workflow gets a typed Jev Choice (invoice or general) and routes each inbound email to the matching handler.
• unclutter - Browser tooling: WXT extension where Jev decides per page element whether it is clutter, removing it under reusable template rules.
• typesafe-adblock - Browser tooling: Chrome extension that asks Jev whether each DOM element is an ad, turning ad blocking into a stream of per-element typed questions.
• DiffJury - Code review: routes each pull request by risk with Jev before a human reviewer is assigned, doubling as a review coach.
• HA-Jev - Smart home: Home Assistant integration that answers questions about the house as a probability, a choice, or a score.
• secondlayer - Fault triage: self-hosted Stacks data service whose Slack gate and fault-triage paths both run on Jev decisions.
• new-api-typesafe-plugin - LLM gateway: adds a native /v1/systemone endpoint to new-api so typed decisions sit behind the same gateway as chat models.
• duet-agent - Agent harness: keeps a Jev-backed routing table for deciding which model should serve a request.
• json-render - Generative UI: Vercel Labs' UI framework uses Jev in its compose path to pick which components and actions a rendered interface should contain.
• omo-jevlike-router - Skill routing: shrinks the skill catalog in a system prompt with one forward pass over a frozen Qwen, routing each request Jev-style.
• jev-cookbook - Developer education: 15 runnable Node recipes that route support tickets, file documents, categorize bank transactions and label Gmail with Jev Choice and Noul questions, sending low-confidence answers to human review.
• flue-jev-demo - Agent routing: routes a Flue agent's work with Jev through Cloudflare AI Gateway.
• sift - Content labelling: Chrome extension that labels every post in an X timeline - substance, humour, chit-chat, promo, junk, or AI-written - with Jev decisions.

Verification & Guardrails

Source file: categories/verification-guardrails.md

• is-malicious - Software supply-chain security: asks Jev Noul checks about source and build files, escalates suspicious chunks for a second pass, and returns implicated files and lines before execution.
• jev-review - Software engineering: staged code-review workflow and local dashboard where Jev gates each review stage before a change advances.
• pi-jev - Agent safety: adds a measured tool-call gate to the Pi coding agent so risky calls are checked by Jev before execution.
• OpenWork - Engineering workflow: wires Jev into its eval testkit as a verification judge so agent-produced work is gated by typed verdicts rather than a text model.
• jev-guard - Agent security: prompt-injection and dangerous-action guard for Claude Code, Codex, Pi, and ACP agents, with Jev deciding what to block.
• Foreman - Software factory: sits above Codex workers and has Jev independently judge whether an implementation is complete, its tests sufficient, or a human is needed.
• stanley-code - Coding agents: bounded Jev workflows that keep agent judgments typed instead of free-form.
• opencompany - Agent workspace: runs its approval review through Jev so workspace actions are gated by a typed decision.
• jev-git - Developer tooling: sub-second Git pre-commit & pre-push reflex gate that screens staged diffs for secrets and destructive commands using Jev.
• pi-heed - Runtime constraints: checks every side-effecting tool call from the Pi agent against what the user actually asked for.
• Hunch - Code review: plain-English rules that Jev checks code against, locally or on every pull request, with Jev picking one label per finding.
• Abide - Agent supervision: reads every edit a coding agent makes and has Jev flag rule violations, with the project reporting that an independent reviewer confirmed 10 of the 39 flagged edits and 11 of the 15 flagged turns.
• fx - Coding agent: ships a typesafe_permission_reviewer builtin so the agent's permission decisions run through Jev rather than an LLM call.
• Sniff Test - Writing: prose linter that asks Jev ten Boolean questions per paragraph (stacked hedges, restating closers, not-X-but-Y turns, naked cost figures) at a 0.7 threshold; CLI, pre-commit hook, GitHub Action and Claude Code skill; measured 182 ms median and 1 of 54 clean paragraphs flagged against 37 for Haiku 4.5.
• jev-pref - Code review: turns the preferences in a project's AGENTS.md into jev-pref.json rules that Jev checks against each diff hunk, staged file set, or pull request, returning fix_now or advisory findings to the coding agent and a nonzero exit code on blocking ones.
• jev-axi - Agent safety: PreToolUse gate for Claude Code and Codex that has Jev score each shell command for destructiveness, exfiltration, remote code execution, and security weakening, deciding routine commands locally so nothing is sent for them, and scoring 44/44 on the 44 labeled tool calls in its repository.
• pi-verdict - Agent safety: Pi permission gate where Jev answers one Choice (allow/ask/deny) per gray-zone tool call — deterministic rules settle clear cases first, deny blocks, ask escalates to a human confirm, and errors or timeouts deny; Jev is an optional backend, OpenRouter-only and experimental.
• jev-commit - Developer tooling: pre-commit hook where one Jev call judges whether the commit message matches the staged diff, flags debug leftovers and unmentioned work, and blocks only on a detected credential.
• Blink - Code review: CLI that coding agents run after every change, with Jev checking the diff near-instantly in place of an LLM reviewer.
• hermes-jev-approvals - Agent approvals: proof of concept that puts Jev in front of Hermes Agent's command approvals, reporting 8.7x faster decisions and 4.4x fewer prompts to the user.

Scoring & Ranking

Source file: categories/scoring-ranking.md

• Clean Code Judge - 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 - 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-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 - 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.
• pagegrade - Content quality: grades page sections for clarity, writing, and on-page SEO with Jev and returns per-section scores.
• jev-scout - Developer tooling: sub-second zero-hallucination open-source repo and crate scout using TypeSafe Jev speculative fan-out scoring.
• 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 - 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.
• SemanticSpace - Semantic mapping: places phrases in 2D by asking Jev how strongly each one relates to two chosen axis concepts and using those scores as coordinates.
• Supercov - Code quality for coding agents: Jev answers twelve Noul properties per source file so the agent knows what to fix first.
• 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 - 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-skip - 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.

Agent Decisions

Source file: categories/agent-decisions.md

• jev-social - Social media research: uses a Jev Choice at each step to select a concrete socai CLI operation and observed post or profile target on Instagram, TikTok, or LinkedIn, rejecting malformed or low-confidence decisions before execution.
• Jev Ultrafast - Browser automation: browser-use's ultrafast agent where Jev decides each next action and element to click, calling a language model only when text must be typed.
• jev-agent-browser - Browser agents: a parent agent delegates bounded tasks to a Jev loop that selects typed browser actions, validates them through agent-browser, and escalates ambiguity or stuck states back to the parent.
• pi-typesafe-jev - Coding agents: exposes System One judgments as five Pi tools so a model makes narrow semantic judgments while code and users keep control of thresholds, weights, and actions.
• jev-judgment - Coding agents: agent skill that sends closed coding-agent judgments to Jev so verdicts stay typed, cheap, and comparable across runs.
• limpet - Coding agents: Stop hook that keeps an agent from finishing too early by judging plain-language completion rules with Jev.
• robo-harness - Robotics: SO-101 arm workbench where a Jev decision runner picks bounded joint steps from typed candidate actions under a spend budget.
• dsh-auto-mode - Coding agents: DeepSeek Harness permission preset whose end-prompt step has Jev answer the open questions an agent leaves in its final message, steering them back only when a choice clears 0.6 confidence and an autonomy-safety Noul clears 0.5, and returning the turn to the human otherwise.
• augustus - Coding agents: agent skill that maps Choice, Score, and Noul onto classical methods so an agent can place typed judgment in software, with a composition algebra, question-design diagnosis, and a validation gate that requires a falsifying experiment.
• yoshi - Context management: proxy for Claude Code and Codex where Jev judges which conversation history is still needed before pruning.
• pi-jev (TheoOliveira) - Coding agents: semantic tool routing and typed System One decisions for the Pi coding agent.
• pi-quiet-ask - Coding agents: gives the Pi agent a quiet Jev decision layer for judgments it would otherwise hand to a chat model.
• fastbrowse - Browser agents: Jev picks each action from what is on the page while an LLM reads and plans.
• super-jev - Decision harness: turns a Jev answer into a bounded action instead of leaving the caller to interpret it.
• jev-superpowers - Systematic software development framework for AI coding agents upgraded with TypeSafe Jev System One typed decisions, zero-hallucination package vetting, and completion gates.
• Jev Browser - Browser automation: drives a browser with Jev deciding each step, pitched as fast and very cheap next to LLM-driven browsing.
• pi-fast-jev-compaction - Context management: Pi extension that keeps conversation text verbatim while pruning stale tool history with Jev, falling back to Pi's own summarization only when pruning cannot free enough room.
• Atomic - Coding agent runtime: ships a first-class Jev structured-output provider so an agent's decisions come back typed, through the same decision resolver as its other providers.
• fast-jev-compaction - Context management: Claude Code plugin that replaces the compaction summary with Jev decisions, scoring every tool call and result for whether it is still needed instead of summarizing the session.
• fast-dev-compaction - Context management: Codex port of the Jev-guided compaction idea, restoring context verbatim around a session compaction rather than summarizing it.
• public-browser - Browser control: lets Claude Code and Cursor drive a real Chrome profile, with a Jev loop deciding the actions, reporting roughly 30% fewer tokens and 25% lower cost.
• pi-typesafe-router - Coding agents: routes Pi's work through typed Jev decisions.
• wakegate - Long-running agents: before a sleeping agent's LLM is resumed on a timer or incoming event, Jev answers a Choice (wake, not yet, unrelated) against the agent's own sleep note, and code skips the wakeup only when wake is below 0.2 while always waking on user messages, bare timers, a skip limit, errors, and timeouts; one run passed 21 of 21 hand-written scenarios, which the README calls a smoke test rather than a benchmark.
• BrowserClaw -