questions: { direction: choice, }
jev-trader
One AI trade decision every Monad block. Jev on Kuru MON-USDC.

Every project here really calls Jev in its source · refreshed daily
questions: { direction: choice, }
One AI trade decision every Monad block. Jev on Kuru MON-USDC.
questions: { requested: boolean, issued: boolean, route: choice, // +1 }
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
questions: { intent: choice, is_urgent: boolean, frustration: score, }
Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.
questions: { department: choice, return_reason: choice, requested_resolution: choice, // +2 }
tiny Jev-like model built on top of Qwen2.5-0.5B you can train and run on your MacBook
questions: { correctness: boolean, security: boolean, reliability: boolean, // +2 }
A staged code-review workflow and local dashboard built with TypeSafe Jev.
questions: { action: choice, done: boolean, risk: boolean, }
把 Computer Use 的「下一步点哪里」交给 Jev(TypeSafe System One):Jev 从界面文字候选中选元素、动作、完成度与风险,Codex Computer Use 负责读取界面与执行,本地策略门槛拦截敏感操作。只传文字,不传截图。
Write your own criteria, options and score levels in the playground, paste some text, and watch Jev decide. 15 free runs a day.
questions: { direction: choice, }
One AI trade decision every Monad block. Jev on Kuru MON-USDC.
questions: { requested: boolean, issued: boolean, route: choice, // +1 }
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
questions: { intent: choice, is_urgent: boolean, frustration: score, }
Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.
questions: { department: choice, return_reason: choice, requested_resolution: choice, // +2 }
tiny Jev-like model built on top of Qwen2.5-0.5B you can train and run on your MacBook
questions: { correctness: boolean, security: boolean, reliability: boolean, // +2 }
A staged code-review workflow and local dashboard built with TypeSafe Jev.
questions: { action: choice, done: boolean, risk: boolean, }
把 Computer Use 的「下一步点哪里」交给 Jev(TypeSafe System One):Jev 从界面文字候选中选元素、动作、完成度与风险,Codex Computer Use 负责读取界面与执行,本地策略门槛拦截敏感操作。只传文字,不传截图。
questions: { refund: boolean, spam: boolean, }
Turn any open model into a classifier/jev endpoint
questions: { next_action: boolean, danger: score, }
A TypeSafe/Jev agent that plays Super Mario Bros. from structured emulator state.
questions: { window: choice, source_reddit: boolean, plain: boolean, }
Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.
questions: { positive: boolean, }
Drop-in TypeSafeClient replacement backed by LLM APIs
questions: { billing: boolean, }
The official Python library for the TypeSafe API
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.
questions: { severity: score, needs_tool: boolean, }
A lightweight Jev-powered router for models, tools, and subagents
questions: { destructive: boolean, exfiltration: boolean, beyond_scope: boolean, // +1 }
TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers
questions: { urgency: score, }
A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.
questions: { queue: choice, escalate: boolean, urgency: score, // +1 }
A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
questions: { risk: score, }
Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz
questions: { stale: choice, }
Bounded TypeSafe Jev workflows for coding agents.
questions: { intent: choice, needs_reasoning: score, }
The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
questions: { relevant: boolean, }
Classify first. Read selectively. A portable agent plugin and MCP tool for batch text classification.
questions: { urgent: boolean, }
Ruby client for decision models such as Typesafe Jev
questions: { ok: boolean, }
Chrome extension: vibe-check your X posts with TypeSafe's Jev before you hit Post
questions: { sentiment_spectrum: score, catalyst_impact: score, }
An on-demand crypto market intelligence and decision-support terminal powered by TypeSafe AI's System One model (Jev).
questions: { refund: boolean, }
This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
questions: { department: choice, urgent: boolean, frustration: score, }
OpenDecision is an open-source semantic decision engine like typesafe's jev.
questions: { intent: choice, reuse_cache: boolean, needs_subagent: boolean, // +2 }
Connect TypeSafe Jev to Grok Bot as a cheap decision layer - usage gates, skill template, examples
questions: { refund: boolean, team: choice, }
ACP and MCP adapter that bridges TypeSafe Jev with any LLM — computer use and typed decisions alongside Codex, Claude, Grok, and OpenCode.
questions: { next_reference: choice, }
A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
questions: { problem: score, customer: score, demand: score, // +5 }
Describe your startup idea. Jev decides: kill it, fix it or ship it.
questions: { ok: boolean, }
MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client
questions: { r0_missing: boolean, r0_instruction: boolean, }
Context-pruning proxy for Claude Code and Codex: Jev judges which history is still needed, measured not claimed. POC here now, heading soon into https://github.com/compozy/compozy
questions: { is_billing: boolean, category: choice, }
Semantic tool routing and typed System One decisions for the Pi coding agent using TypeSafe Jev
questions: { stuck: boolean, destructive: boolean, }
TypeSafe AI の System One モデル Jev を MoonBit から触るためのプレイグラウンド。
questions: { injection: boolean, hidden: boolean, exfiltration: boolean, // +3 }
Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
English full-duplex voice control for macOS with OpenAI Realtime, native Accessibility, and Jev.
questions: { questions: boolean, }
Jev-powered conversation memory: find past sessions and revisit decisions with original sources. A macOS workspace for OpenAI Codex. Manage AI conversations and agents, explore code with CodeGraph, and work with Git, Ghostty terminals, and Apple Notes in one app.
questions: { binary: boolean, rating: score, }
Replicating Jev with a local LLM
questions: { conflict: boolean, }
Community TypeSafe AI playground: 110 use cases, games, dilemmas and model challenges, with editable prompts, A/B comparisons and a mobile-friendly UI.
questions: { s0: boolean, s1: boolean, }
Lint rules written in plain English. Oxlint finds the code, TypeSafe Jev answers the question.
questions: { color: choice, }
Open-source macOS AI computer use and native GUI automation on Apple silicon. Jev + OmniParser CoreML + Apple Vision OCR. Bring your own OpenRouter, Vercel AI Gateway, or TypesafeAI token.
questions: { does_pass: boolean, }
Using Jev as an evaluator.
questions: { value: choice, surprising: boolean, funny: boolean, // +4 }
YouTube transkriptlerini anlamına göre keşfedin. Türkçe arayüz, Jev analizi, altyazı dışa aktarma ve Vercel kurulum rehberi.
questions: { movement: choice, start_jump: boolean, ceiling_hop: boolean, // +1 }
A uv-managed Python prototype that plays NES Super Mario Bros. (level 1-1 by default).
questions: { action: choice, in_danger: boolean, threat: score, }
Experiments in driving real-time games with TypeSafe Jev: a fast
questions: { amount_disclosed: boolean, }
A browsable directory of what Jev can do — 50 runnable
questions: { directed: boolean, kind: choice, }
Auto mode for every coding agent, built on Jev: risk-scores every tool call with session context (deny / ask / allow), flags prompt injection in results, checks skills and plugins. Claude Code, Codex, Copilot, Gemini, Cursor, pi, OpenCode, ACP.
questions: { is_urgent: boolean, department: choice, frustration: score, }
Jev decision layer for agents: MCP server, embeddable DecisionModel library, and an escalate-only Claude Code plugin (TypeSafe AI's Jev)
questions: { team: choice, human_requested: boolean, refund_requested: boolean, // +3 }
Interactive experiments with TypeSafe Jev, from support routing to 3D driving simulations with real AI decisions and visible sensor inputs.
questions: { skill: choice, }
Jev-assisted file retrieval and request caching for faster Pi workflows
questions: { route: choice, }
Jev-powered Instagram, TikTok, and LinkedIn research: typed routing, real browser evidence, streamed post cards, video capture, and cited socai reports.
questions: { noul: boolean, }
typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
questions: { lane_action: choice, speed_action: choice, hazard: score, // +1 }
2D autonomous car simulation in the browser, driven by TypeSafe's Jev decision model
questions: { route: choice, urgent: boolean, severity: score, }
Nemotron Diffusion Decision Lab
questions: { claims_done: boolean, claims_verified: boolean, verification_applies: boolean, // +1 }
Claude Code Stop hook that blocks an unverified done: reads the transcript for evidence, asks Jev once, fails open on everything else
questions: { route: choice, toolFree: boolean, }
Jev-native AI security harness for autonomous research, multi-agent swarms, persistent hunt boards, and long-running agent workflows. CLI-first, open source, and built for authorized security research.
questions: { intent: boolean, }
TypeSafe Jev as the pi coding agent's quiet decision layer
questions: { intent: choice, rage_bait: boolean, synthetic: boolean, // +1 }
在 X 的时间线上,给每条帖子标出它想让你干什么。判断来自 Jev,一个只返回概率、不生成文本的模型。
questions: { actionable: boolean, priority: choice, value: score, }
Open-source Jev log triage for OpenTelemetry. Score the signal before expensive LLM analysis.
questions: { is_bug: boolean, team: choice, urgency: score, }
Claude Code / Codex / pi plugin that hands agent steps needing no text output to Jev (TypeSafe's judgment model) — measured p50 ~230 ms and ~$0.02 per 1,000 judgments, with typed escalation back to the LLM
questions: { topic: choice, }
Evidence-backed use cases, patterns, and guidance for building with Jev, TypeSafe AI's System One model. Every claim is labeled and sourced.
questions: { category: choice, urgency: score, isPersonal: boolean, }
Open-source AI email triage for Gmail. Sorts your inbox into Needs reply, Updates, Promos, Sales and Spam with Jev, TypeSafe AI's decision model, via Vercel AI Gateway. Read-only, runs locally, 1,000 emails in about a minute for 3 cents.
questions: { unambiguous_match: boolean, }
Policy-bounded Jev target selection for resilient Playwright workflows
questions: { call_t1: boolean, }
Verbatim Jev-scored context reduction for omp, over TypeSafe or OpenRouter
questions: { intent: choice, isUrgent: boolean, }
Flue agent routing with TypeSafe Jev through Cloudflare AI Gateway
questions: { a: boolean, b: boolean, }
Inspired by TypeSafe Ai, Ask a local LLM typed questions, get calibrated probabilities instead of text. Structured output without generation or parsing. MLX / Apple Silicon.
questions: { billing: boolean, urgency: score, }
A small async LangGraph workflow that sends a mocked email to TypeSafe's Jev model,
questions: { context_needed: choice, }
Pi coding-agent extension: TypeSafe Jev checks for tool calls, tool outputs and replies (prompt injection, approvals, secret scrubbing, task pinning)
questions: { beauty: boolean, cat: choice, }
grep for what code does, not what it's called. Semantic code search powered by TypeSafe Jev.
questions: { irreversible: boolean, goal_done: boolean, }
AskJev — Jev autopilot for any website + guard on irreversible clicks (TypeSafe System One, not Claude)
questions: { partial: boolean, score: boolean, }
A fast browser agent: Jev picks each action from what is on the page, an LLM reads and plans, and every claim in an answer cites a quote from the page.
questions: { urgent: boolean, }
Connect JEV to MCP clients and compare its judgments against general-purpose LLMs using shared datasets and measurable accuracy.
questions: { category: choice, tech: boolean, ai_written: boolean, }
Chrome extension that labels every post on X (Substance · Humor · Chit-chat · Promo · Junk · AI-written) with TypeSafe Jev, and hides the ones you don't want.
questions: { q1: boolean, }
A small, extensible decision-to-action harness for TypeSafe Jev
questions: { is_spam: boolean, }
Run a JSON Schema through TypeSafe's Jev API, and get JSON back.
questions: { instructions: boolean, }
TypeSafe Jev routing for Oh My Pi, with an opt-in checkpoint orchestrator and editable XDG configuration. Requires Bun = 1.3.14 and OMP = 18.2.3.
questions: { odd: boolean, }
Check whether a number is odd, using a System One model, with a calibrated probability.
questions: { throttle: choice, yaw: choice, pitch: choice, // +3 }
This demo uses Jev from TypeSafe AI to autonomously fly a drone in a random city from point A to point B, avoiding obstacles along the way. A trip costs $0.01.
questions: { unsolicited_promotion: boolean, profile_bait: boolean, scam_or_phishing: boolean, // +5 }
Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev
questions: { operation: choice, }
Jev for Chrome: drives the tab you are looking at with TypeSafe Jev, a sub-second decision model. Community port of browser-use/jev-ultrafast, not affiliated with TypeSafe.
questions: { about: boolean, keep: choice, }
TypeSafe System One / Jev community directory — GitHub projects & posts around typed decisions (typesafe.ai)
questions: { is_spam: boolean, folder: choice, suspicion: score, }
Jev Explained
questions: { connected: boolean, }
Jev DSH 决策引擎|面向 Agent Harness 的结构化决策插件。原生支持 DeepSeek Harness,通过 iPolloWork 支持 OpenCode、Codex Harness。
questions: { operation: choice, click_target: choice, goal_reached: boolean, // +1 }
Fast, bounded browser agents powered by Jev and agent-browser — typed actions, research, classification, and safe orchestration.
questions: { department: boolean, frustration: boolean, }
Ruby client for typesafe.ai
questions: { delivery: boolean, department: choice, urgency: score, }
Adapt local language models into Jev-compatible structured decision engines with Choice, Score, and Noul outputs powered by prefill-only binary inference.
questions: { done: boolean, }
A chatbot from typed Jev decisions: hierarchical speculative decoding over System One probabilities.
questions: { is_impossible: boolean, }
Jev-powered decision layer for DeepSeek Harness
questions: { is_urgent: boolean, frustration: score, }
Claude Code plugin that scores review findings, debug hypotheses and design options with TypeSafe's Jev — calibrated probabilities instead of one more opinion.
questions: { is_urgent: boolean, }
Agent-facing TypeSafe Jev (System One) for the DSH Web GUI. The model itself
questions: { routine: boolean, }
SQL with natural-language predicates, powered by TypeSafe's Jev. Filter, rank, classify and score rows by meaning — batched, cached and cost-guarded.
questions: { automated: boolean, }
A small Chrome extension that marks or collapses likely AI-written replies on X, powered by Jev.
questions: { done: boolean, blocked: boolean, }
jev-browse is an unofficial project and isn't affiliated with TypeSafe or Vercel.
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
Türkçe ve İngilizce doğal konuşmayla Windows 10/11 bilgisayar kontrolü: OpenAI Realtime, local Whisper, Jev, UI Automation ve Playwright.
questions: { department: choice, frustration: score, is_urgent: boolean, }
DSH bundle that registers jev_ask for TypeSafe Jev noul, choice, and score answers.
questions: { instructions: boolean, }
Runtime constraints for the pi coding agent: checks every side-effecting tool call against what you said, before it runs. Powered by TypeSafe Jev.
questions: { urgent: boolean, }
The decision layer for your Rails app. A Rails-native wrapper around TypeSafe's Jev System One API: typed, calibrated decisions in your control flow.
questions: { what: choice, }
Operator lab for TypeSafe Jev. Chess Arena, closed-schema booths, Stockfish HUD for review only.
questions: { t: boolean, }
Your feed, your rules, in plain English. A browser extension that filters X, YouTube, Reddit, LinkedIn and Hacker News with topics you write yourself. Bring your own Jev key.
questions: { model: choice, effort: choice, is_followup: boolean, }
Local proxy that picks the Claude model and effort per message using TypeSafe Jev. Routes subagents, leaves your cached main chat alone.
questions: { needs_skill: boolean, }
Claude Code mod that routes decisions to TypeSafe's Jev model: ranks installed skills per prompt, and answers the agent's own this-or-that questions when confident.
questions: { confidentiality: choice, }
JEV Document Classification enables the rapid and cost-effective classification of text-based documents using AI, leveraging TypeSafe's "System One" model.
questions: { comparison: choice, }
Jev powered OpenCode compaction
questions: { blocking: boolean, }
Input moderation for Mastra agents on TypeSafe Jev — one file
questions: { department: choice, }
Measure when to use Jev and other models on your data, then route accordingly.
questions: { content_type: choice, }
Fast structured Android control loops with TypeSafe Jev and Mobile MCP
questions: { is_command: boolean, complete: boolean, }
Draw on a tldraw canvas with your voice and a pointing finger. Jev (TypeSafe System One) decides action, target and place in ~350 ms per spoken word.
questions: { department: choice, frustration: score, is_urgent: boolean, }
Jev-compatible System 开源Jev
questions: { requires_uncertainty_notice: boolean, response_depth: score, }
A polished OpenAI + TypeSafe Jev terminal interface for answers with transparent decision reports
questions: { verdict: choice, should: boolean, doom: score, // +1 }
We ask Jev, TypeSafe AI's System One model, whether AI should kill us all. Every ten minutes. Using the actual headlines.
questions: { difficulty: score, needs_reasoning: boolean, stakes: score, // +5 }
Shift every LLM call to the cheapest model that can handle it. Routing decided by TypeSafe Jev in ~180 ms. No training data. Policy in plain YAML. TypeScript and Python.
questions: { category: choice, reached_assertion: boolean, missing_context: boolean, }
Open-source Codex plugin for TypeSafe Jev decision consultation, failure diagnosis, and evidence-based completion review
questions: { is_toxic: boolean, is_profane: boolean, severity: score, // +2 }
Fast, drop-in profanity and toxicity screener for Node.js, powered by TypeSafe AI Jev. Catches leetspeak, character spacing, and romanized profanity across languages including Kannada, Telugu, Tamil, Hindi, and Bengali. ~50-500ms latency.
questions: { complexity: score, needsPlanning: boolean, }
Throwaway Jev demo: route coding tasks to Grok Build or Codex Astra
questions: { ping: boolean, }
Codex plugin: Jev-guided dieting of bulky tool results
questions: { task_completion: score, instruction_following: boolean, grounded_in_evidence: boolean, // +5 }
Affordable for parallel online agent evals and observability. Powered by JEV.
questions: { is_billing: boolean, }
Build versioned judgment functions on TypeSafe's Jev once, then call the same published version from your backend over HTTP and from coding agents over MCP. The vendor key stays on your machine.
questions: { complete: boolean, }
Open-source native computer use for macOS and Windows: TypeSafe Jev, local OCR, and selective planning.
questions: { wants_refund: boolean, intent: choice, }
Runtime authorization and guardrails for AI-agent tool calls with deterministic policy and TypeSafe Jev via OpenRouter.
questions: { operation: choice, }
Manipulate images via chat, uses Jev like model to classify prompt
questions: { destructive: boolean, exfiltration: boolean, privilege: boolean, // +4 }
Open auto mode for AI agents — a calibrated tool-call firewall powered by TypeSafe Jev. Ships as a Claude Code hook
questions: { enabled: boolean, color: choice, progress: score, }
Local JEV-style decisions with DiffusionGemma on Apple Silicon, with benchmarks and coding-agent examples.
questions: { category: choice, bug_severity: score, has_repro_steps: boolean, // +2 }
MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code
questions: { action: choice, }
Jev and Microsandbox explore alternate game futures with a reusable TypeScript learning harness
questions: { content_type: choice, already_known: boolean, insight_density: score, }
Know before you click. A Chrome extension that reads articles and YouTube videos ahead of you and says read, skim, save, or skip — with a confidence, tuned to your goals. Open source, MV3, powered by Jev.
questions: { completion: choice, }
One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.
questions: { relevant: boolean, category: choice, }
PiJev: a terminal coding agent with Jev in the loop — Jev ranks the repository's files before the first call, picks skills and triages failures; your coding model writes the code. Built on Pi.
questions: { hallucination_sensitive: boolean, }
Type-safe model router. Jev (System One) banks each request to a typed catalog route.
questions: { ping: boolean, }
Yunus Pi is a heavily customized harness experience built on top of a forked Pi harness (pi.dev). It uses patches, extensions, skills, and custom provider configs to customize the overall experience. It uses advanced machine learning, Jev, Cactus Needle 3 and similar technologies.
questions: { criteria: boolean, }
Jev-powered Chrome extension that categorizes X posts and classifies replies in context.
questions: { claims_success: boolean, }
Find the AI agent runs that broke because their environment did: missing keys, tools, files, permissions, network, or context. Powered by TypeSafe Jev.
questions: { label: choice, }
Owned, deterministic classifier for checking whether agent claims are supported by evidence, with optional Jev comparison through Cloudflare AI Gateway.
questions: { irreversible: boolean, }
Pydantic AI capabilities made stronger with Jev: small runnable demos, one file each
questions: { composition: choice, legibility: boolean, }
Image-native typed decisions with shared visual encoding and Qwen3-VL
questions: { is_urgent: boolean, severity: score, }
Shadow-mode validation harness for a pre-execution firewall on AI agent tool calls (TypeSafe/Jev). Real run, findings in report.md.
questions: { action: choice, asset: choice, condition_operator: choice, }
Reference prototype exploring agentic commerce: TypeSafe/Jev → Axiom → Argent → Silverscript on Kaspa.
questions: { tier: choice, is_greeting: boolean, }
Jev (TypeSafe) model router on the Vercel AI Gateway
questions: { line: choice, pace: choice, overtake: boolean, // +1 }
Uses jev to control race cars on a virtual track
questions: { severity: score, area: choice, }
An eval-first MCP server for TypeSafe's Jev, a System One model that returns typed judgments (noul, choice, score) with probabilities instead of generated text.
questions: { destructive: boolean, secrets: boolean, }
Jev-powered Judgment layer for Claude Code. Stops paying reasoning prices for if-statements: a PreToolUse hook scores every tool call against a YAML policy you own — allow / deny in ~100 ms, no LLM in the loop. TypeSafe Jev now, local models next. Dry-run by default, calibration table published.
questions: { is_exquisite_and_dynamic: boolean, animation_verdict: choice, primary_deficiency: choice, }
Real-time quality gate and Art Director Warden for Claude Code powered by TypeSafe Jev 1.13 non-autoregressive decision model
questions: { person_name: boolean, email_or_phone: boolean, postal_address: boolean, // +5 }
CLI that finds PII in text with TypeSafe Jev: presence, sensitivity, and located spans
questions: { is_regulation: boolean, mentions_deadline: boolean, mentions_fines: boolean, // +5 }
Never confidently wrong: a TLA+-verified consensus kernel around TypeSafe's Jev, run through 1,680 chaos-tested pharmacy decisions with zero wrong verdicts. Film, code, and every captured call.
questions: { topic: choice, requests_credentials: boolean, sender_identity_mismatch: boolean, // +4 }
Experiments on TypeSafe Jev (System One decision model) via OpenRouter: repeatability, perturbation, and LLM baseline comparison
questions: { needs_rewrite: boolean, visual: choice, }
Pi extension: clearer replies via Jev review + optional rewrite/visuals
questions: { states_application_instruction: boolean, }
Upwork job classification example
questions: { a: boolean, b: boolean, }
A Chrome extension that brings TypeSafe's Jev to X.com to analyze posts as you browse
questions: { is_urgent: boolean, department: choice, }
Opencode plugin using Jev (system one model) as part of software development process. Not affiliated with Opencode team.
questions: { file_removal: score, credential_theft: score, data_exfiltration: score, // +5 }
Static shell script analysis with Jev.
questions: { kind: choice, relationship: choice, review_priority: score, }
面向开发者的 Jev / TypeSafe 精选:说明每个项目里 Jev 负责哪一步、先读哪段源码、需要什么依赖,以及哪些结论还没有运行验证。
questions: { uses: boolean, }
Configurable GitHub submission review and PR classification with TypeSafe Jev. No text-generation model.