Typesafe GitHub Repositories (2026) · Open Source Tools

🚀🚀 A multimodal System One decision model that gives calibrated answers to typed questions about screens, photos, video and text in one forward pass.

🤖 A client-first, server-capable, fully type-safe router and full-stack framework for the web (React and more).

Claude Code skill: hand bulk judgment calls to Jev. 86% fewer Claude tokens on a 12-task benchmark, up to 20x faster. One-line npx install.

A curated list of decision models (System One / typed decision models): hosted APIs, open-weight models, runtimes, SDKs, applications, benchmarks, and papers.

A modular and open-ended toolkit for WebGPU, with advanced type inference and the ability to write shaders in TypeScript

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Coverage, security and code quality for coding agents

Guardrails for Pi that steer instead of interrupt: enforces your project rules on every write, holds only hard-to-undo actions (3 per 1,000 calls, measured on real sessions), catches unverified "done" claims and stuck loops, and trims tool output. Built on pi-typesafe.

A community directory of projects built on Jev, TypeSafe AI's System One model.

TypeSafe Jev for DeepSeek Harness, the Model Context Protocol, and plain Node: typed judgments instead of prose, offline by default.

Unofficial TypeSafe Jev showcase — System One decisions, not chat.

mu (μ): most of what a coding agent decides isn't code. mu hands 40 kinds of yes/no calls to a small model: fewer wasted tokens, fewer approvals on autopilot, fewer runs that stop halfway. Built on pi.

ACP and MCP adapter that bridges TypeSafe Jev with any LLM — computer use and typed decisions alongside Codex, Claude, Grok, and OpenCode.

The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.

grep, but the pattern is a description. Filters lines by meaning with TypeSafe's Jev decision model: ~200 ms and a thousandth of a cent per line.

Go SDK and CLI for TypeSafe Jev: typed decisions (yes/no, choice, score) from a model

Computer use for about $0.0002 a step: OCR the screen, classify the next action with TypeSafe, click. macOS.

Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.

Typesafe APIs Made Simple 🪄

⚙️ A dependency injection toolkit based on Go 1.18+ Generics.