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Claude Code + Codex CLI plugin that verifies the agent follows project rules through a System One (Jev) model

A local MCP server that uses TypeSafe Jev to confidence-gate an AI agent’s next step, routing uncertain decisions to proceed, deeper review, or human input.

jevkit: fast typed decisions for agents. CLI and MCP tools (route, triage, guard, grep, rank, compact, judge) on TypeSafe Jev. Zero dependencies.

Local model-routing proxy where Jev selects the model route and reasoning depth, and also judges which tool history can be compacted.

Jev (TypeSafe System One) decision tools + live verification benchmark for DeepSeek Harness: jev_decision (choice/score/noul) and jev_verify, honest by design.

Claude Code plugin: asks TypeSafe Jev which installed skill fits each prompt and logs the answer (shadow-first). A working reference for the skill-suggestion cookbook on Claude Code — the README records why it is unlikely to help a strong model as a router.

MCP-first toolkit for TypeSafe/Jev — the System One decision model. One stdio server (jev mcp) serves any MCP-capable harness, backed by one local event log and Prometheus impact metrics you can scrape into your own Grafana.

Unofficial MCP server for Jev (Typesafe AI)

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.

Jev-routed client for NEAR AI Cloud inference and IronClaw agents.

MCP server for typed decisions with Jev / System One via OpenRouter or TypeSafe

Shadow-mode validation harness for a pre-execution firewall on AI agent tool calls (TypeSafe/Jev). Real run, findings in report.md. No repository-level license file was found during review.

Agent skill and CLI that turn natural language, an LLM prompt, or the code that runs one into a TypeSafe Jev decision: typed state, Choice/Score/Noul questions, and a runnable script

DSH bundle that registers jev_ask for TypeSafe Jev noul, choice, and score answers.

TypeSafe Jev (System One) decision tools for Hermes Agent: jev_check / jev_route / jev_score / jev_evaluate

Natural-language MCP tool dispatcher powered entirely by TypeSafe's Jev — no general-purpose LLM. Discovers a simple MCP server's tool signatures at runtime and uses Jev's typed primitives (Choice/Noul) to pick the right tool and extract its arguments straight out of the sentence. No repository-level license file was found during review.

Turn your AGENTS.md preferences into a fast, Jev-powered AI linter.

Catch breaking API behavior hidden in OpenAPI prose with deterministic checks and TypeSafe JEV System One semantic review.

Model performance first. Token savings second. A Pi extension with freshness-aware read dedupe, Jev log filtering, and searchable verbatim recall. Keeps existing message history intact.

LLM router that picks the cheapest model capable of handling a query, using TypeSafe's Jev for fast classification instead of an LLM call.

Software, by reflex. A sentence becomes a call of a small program, chosen by Jev, TypeSafe AI's classifier, and run only when it is sure enough. Reflexes are recipes anyone can write, share and improve. A CLI you talk to, a package manager for reflexes from git, and a TypeScript SDK.

Jev-powered, rule-based grader for text files. Runs every rule against every line in parallel. No skimming, no missed lines.

Block, steer, and "fuzzy lint" with Jev to make agents follow your rules and conventions. CLI, github action, pi package, and more. Built with Effect.

Agent plugin and MCP tool where Jev classifies batches of text so agents can read only the relevant items. No repository-level license file was found during review.

grep by meaning, across languages. TypeSafe Jev scores every line against a meaning; combine meanings with AND/OR/NOT. 意味で探す grep。日本語で英語を、英語で日本語を検索できる

Agent plugin that uses Jev to judge when a coding session should compact its context.

Semantic assertions for pytest: test what your LLM app's output means, judged by TypeSafe's Jev.

Portable System-1 decision layer for agent harnesses with host-owned routing, receipts, replay, and fail-open integrations.

React components that resolve which component to render, how to order a list, and whether to show an affordance — from calibrated judgments returned by TypeSafe's Jev. No repository-level license file was found during review.

High-throughput, robust native DuckDB extension for batched and streaming TypeSafe/Jev classification, scoring, and semantic predicates from SQL.

Natural-language row filtering for MySQL, powered by TypeSafe Jev.

A lightweight, native Swift 6 bridge integrating TypeSafe AI's Jev System One decision model into Apple's Foundation Models framework.

Semantic AI for pandas and Polars: classify text, analyze sentiment, and score DataFrame rows with natural-language questions and full probabilities using TypeSafe Jev.

Semantic decisions as ordinary Ruby — feels?, decide, score, Rails validations and pattern matching powered by Jev

DuckDB extension: typed Jev answers as real SQL types

SillyTavern extension where Jev scores replies against configured narration rules before adding guidance.

Conversational-avatar framework with a Jev gate that judges whether a speaker has finished a turn.

Generative UI framework with an experimental evaluator that lets Jev choose among application-supplied composition criteria.

Coding agent with a TypeSafe judgment provider that uses Jev for typed checks, routing, and workflow decisions.

Local Jev-like typed-decision runtime using ONNX and quantized models for offline CPU inference.