Jev发布帖
Diogo Almeida介绍了Jev,即TypeSafe的结构化决策模型。观看发布影片,并探索原始帖子了解该模型的方法、示例和作者报告的性能。
Diogo Almeida介绍了Jev,即TypeSafe的结构化决策模型。观看发布影片,并探索原始帖子了解该模型的方法、示例和作者报告的性能。
TypeSafe的正式发布公告介绍了实验室,并引导开发者使用Jev。公告包含Diogo Almeida的发布影片和原始介绍。
TypeSafe宣布Jev向公众开放,无需等待列表。官方控制台是将类型化决策应用于自己应用程序的起点。
TypeSafe强调Jev的类型化输出方法:应用程序提供状态和问题,然后根据概率、选择或评分进行操作。相关公告还介绍了Venice API集成。
Start with the Launch Post. Explore four official signals.
286 项资源
AI-assisted summaries and translations. Check original sources for context and performance claims.
Claude代码插件通过Jev决策替换压缩摘要,通过一次快速请求对每个工具调用和结果进行评分,过时的调用会被丢弃或截断,所有保留的内容保持原样。
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浏览器使用中的超快速代理:Jev在一次请求中选择操作和DOM元素;仅当需要输入时,小型LLM才编写文本。
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A developer project providing a local MCP server for running pre-made Jev question packs.
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Rust CLI powered by Jev from TypeSafe.ai that ranks agent skills for the next step using live session context. Includes Claude Code hooks, structured JSON, abstention, and local feedback. Requires a TypeSafe API key.
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Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell.
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An agent project that enforces policies by judging Claude Code tool calls.
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Typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
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Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it.
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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.
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Scans a codebase for covert, deceptive, or data-stealing behavior with Jev, then reports suspicious files and line ranges before the user runs it.
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Agent skill: design judgment-assisted systems with TypeSafe Jev (System One). Maps Choice/Score/Noul onto decision theory, reranking, and routing. Composition algebra, question design, validation gates. MIT.
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Fast structured Android control loops with TypeSafe Jev and Mobile MCP.
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A developer project for the agents shelf featuring a local MCP gateway with Jev tool discovery and a dashboard.
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Daf-jev: composable Python toolkit for TypeSafe's Jev (System One) decision API — question builders, confidence gates, evaluator, calibration, CLI, MCP server, agent skill.
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Standalone Android agent for Mobilerun where Jev makes every decision, with a live React studio and an Uber demo.
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Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.
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WXT browser extension: Jev-powered page clutter removal with reusable template rules.
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Jev-Tool-Runner is a GitHub project where Jev selects developer tools and Codex generates code based on those selections.
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A developer project demonstrates Jev's rapid response to browser tasks, with decisions made in approximately 100 milliseconds.
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A Codex plugin that uses Jev to streamline and reduce excessive tool outputs.
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A developer project for automatic context clearing in Pi without losing conversation history.
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A Jev powered LinkedIn recruiting agent. Watch it browse relevant profiles, save links, and review evidence against your hiring brief.
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One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.
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Vercel's open agent framework, which ships Jev as the default evaluation model in its experimental evaluate path.
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A GitHub project converting agent skills into Oxlint plugins that involve Jev.
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Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground.
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A skill for writing and improving programs that call Jev, TypeSafe's System One model.
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Jev-assisted file retrieval and request caching for faster Pi workflows.
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Proof of concept MCP for Typesafe's new Jev AI model.
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A developer project offering semantic code search for coding agents, benchmarked on SWE-bench Lite.
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MCP server exposing TypeSafe Jev as typed, calibrated judgment tools: classify, score, check, batched ask. Ships as a Claude Code plugin.
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Systematic software development framework for AI coding agents upgraded with TypeSafe Jev System One typed decisions.
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Typed, confidence-aware agent skill routing with TypeSafe Jev.
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Home Assistant Assist conversation agent powered by TypeSafe's Jev (System One) model.
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Data extraction for systematic reviews, quoted from the papers. Ask a trial report and its supplements your extraction form or a RoB 2, ROBINS-I, QUADAS-2 or TIDieR template; Jev points at the lines, every answer is a verbatim quote with its page, you check it and export the table. Files stay in your browser.
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Sub-second Git pre-commit & pre-push semantic reflex gate powered by TypeSafe AI Jev.
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Judge agent steps — ok / retry / escalate / stop via TypeSafe Jev.
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I kept watching coding agents burn context on decisions that aren't hard - triage 400 tickets, tag 600 files, route to one of six teams. jev-mode moves those verdicts to a typed-judgment model. I A/B'd it: 78% fewer tokens, 16x less work-attributable input, accuracy 96.1% vs 93.7%. Python, no deps, MIT.
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Write Cucumber tests with just the .feature file. No step definitions — Jev (TypeSafe AI) resolves each Gherkin step and Playwright runs it.
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Reusable GitHub Action: agent fix loop gated by checks, an AI reviewer, and TypeSafe Jev.
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Minimal agent loop where Jev directs control flow and a LangChain chat model writes argument values and the final response.
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Safety checks for Hermes and other AI agents before they act, ask for approval, or verify a change.
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Using Typesafe.AI to generate diff reviews.
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Single-agent Pi coding coprocessor with Jev semantic gates, baseline-to-current diff review, and append-only observability telemetry.
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Every tool call your agent makes, checked before it runs. A Claude Code plugin that uses TypeSafe AI's Jev to verify each pending tool call against the session plan, then allows it, asks you, or blocks it. Proof of concept.
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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.
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2D autonomous car simulation in the browser, driven by TypeSafe's Jev decision model.
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An agent system that makes one Jev decision per computational step.
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Software Factory Foreman: an agent supervisor that uses Jev decisions to keep coding agents on task.
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Agent Skill: send closed coding-agent judgments to TypeSafe Jev.
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Does a TypeSafe Jev rerank beat embedding search? Graded relevance eval (9,831 pairs, 164 zh/en queries) over the Agent Skills Hub catalog, with the judge-circularity bias measured.
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Utilizing Jev, the RLCD-type model provided by TypeSafe AI, to independently and cheaply judge agentic coding sessions.
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Route HTTP requests by meaning. A semantic router for Hono powered by Jev.
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Non-Autoregressive AI Agent Decision Model. Open-source SOTA alternative to TypeSafe Jev. O(1) Tool Routing & DOM Automation on Qwen3.5-2B .
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A CLI and GitHub Action that assesses code-change risk using deterministic rules and TypeSafe Jev, recommending checks and reviewers before merge.
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A browser-native Doom agent experiment with structured spatial state, composable AI controls, live decision telemetry, and a Chocolate Doom WebAssembly runtime.
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Chrome extension that labels every post you scroll past on X with typed Jev judgments and a live cost counter.
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Throw in a pile of company files and get them classified and organized by department, type, sensitivity, date, counterparty and PII, with an index for AI agents. Powered by TypeSafe's Jev on OpenRouter (17¢ per 1,000 files). Zero-dependency Node CLI + Claude skill + Codex agent.
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基于TypeSafe的Jev(System One模型)的LLM网关的防护机制+模型路由器,包含独立的准确性/校准/延迟评估。标准库Python。
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Grok skill: Jev as a judgment sensor in a builder-agent loop (priors × probabilities → next act).
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Predict another skill's next closed decision with TypeSafe Jev — without running that skill.
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Browser automation with Jev (TypeSafe) as decision model.
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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.
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A flexible and configurable CLI model router using TypeSafe Jev.
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A developer project using Jev for plain-language MCP tool calls without an LLM.
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A local computer-use fast path for Codex and Waku, designed for developers.
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A developer project focused on agent memory, where Jev determines what information is relevant to recall.
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Input moderation for Mastra agents on TypeSafe Jev — one file.
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A developer project for agent classification and selective reading using an agent plugin and MCP tool.
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A moderation system for Mastra agents that processes inputs in a single file.
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Jev is integrated into tools like Noul and Score for MCP applications.
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Practical, tested recipes for TypeSafe's Jev decision model on OpenRouter: support triage, database indexing, file organizing, tagging, taxonomies, dedupe, PII detection, extraction, search re-ranking and a browser agent.
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