AgentScope builds agents around model reasoning and tool use, with context management, event streaming, memory and permission controls. JevClassifierModel integrates the Jev classifier through the TypeSafe SDK within this broader agent framework.
Guardrails & safety
Permission checks, moderation and safety filters for agents. Jev answers an explicit policy question before the action runs.
147 active projects match this task, ordered by traction. Browse other tasks →
The native CLI supports an interactive shell, scripted requests and embedding, with skills, MCP servers and subagents. Jev receives review policy, context and the pending action, returning a clear or caution decision for the permission pipeline.
awesome-jev-by-typesafe collects sourced Jev use cases, prompts, patterns and starter code as an independent community resource. It explains Choice, Score and Noul for classification, routing and verification while keeping control flow in code. Explore Python and TypeScript examples; offline policy tests need no key, while live examples require TYPESAFE_API_KEY.
Jev Review scans Git diffs or complete codebases for correctness, security, reliability, compatibility and test coverage. Jev selects evidence, classifies mechanisms, scores severity and, when needed, uses Choice to select a reviewer. Code applies thresholds and workflow policy. Use Node.js 24+, Git and a TypeSafe key to generate JSON reports or inspect saved reviews locally.
Real-time Discord moderation bot: Jev evaluates messages and metadata in parallel to catch phishing, spam, and social engineering with a progressive escalation ladder.
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.
Typed-judgment admission control at the traffic edge: three-layer prompt-injection and abuse filter for nginx/OpenResty, powered by TypeSafe Jev. Fail-open, cached, hot-reloadable.
Self-evolving cognitive decision engine & TypeSafe Jev alternative. Deliberative decision flywheel ('explore first, crystallize later' System 2→1) with 100% option-order invariance. Typed probabilistic API (Choice, Noul, Score) for Open LLMs, Laya (ModernBERT), & commercial Jev with calibrated logprobs and adaptive safety guards.
A Clash Royale bot with no trained policy: Jev (TypeSafe System One) makes every decision from the live game state
Typed judgment tools for MCP agents. TypeSafe's Jev model as verify, screen, find, classify, rerank, decide, compare, extract, review, gate, and score: the model judges, policy decides auto, review, or escalate.
位于 nginx 与大模型后端之间的前置过滤反向代理:逐请求提取用户输入交给 JEV 判定,有害拦截、正常透明放行
A minimal permission gate for Pi in the style of Claude Code's auto mode
A curated, evidence-led directory of DeepSeek Harness (DSH) plugins: verified loadable extensions, skills, and permission-aware installation guidance.
Compile agent policy prose into deterministic verdict programs: narrow evidence questions for the model, the verdict computed in code. Install: npm i -g jev-compiler
Input moderation for Mastra agents on TypeSafe Jev — one file
Decision maker for Ruby: turn decision model answers into policy verdicts
Fast System-1 Decision, Arbitration & Safety Engine for Autonomous AI Agents (Powered by TypeSafe Jev)
基于 Jev 的聊天决策辅助:读当前聊天窗口,只返回类型化判定与置信度,不生成回复。QQ / 飞书 / 抖音实测可用。· An on-device chat co-pilot built on Jev — typed verdicts instead of prose, no package allowlist.
An automated Discord moderation bot, powered by Jev.
Experimental Jev permission gate for Claude Code via OpenRouter, with reproducible latency and cost benchmarks
Effect-based safety gate for AI coding agents' shell commands (OpenCode, Antigravity): fast structural rules, then TypeSafe's Jev or a chat model judges what a command does. Certified with Jev at zero dangerous commands allowed.
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.
Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go
A governed execution layer between typed-decision models (TypeSafe Jev) and agent/AI tooling like Claude Code, MCP, and AI SDKs, turning probabilistic decisions into deterministic, policy-controlled, and auditable actions.