Jev agents, skills & apps

An input that turns into a task, event or other UI card. Jev classifies intent and signals; deterministic code extracts dates and values. An offline keyword classifier is also available.

A workbench for screening datasets with Jev, training a separate model and inspecting saved decisions and evaluations. Its public demo uses local rules and a small statistical model, not live Jev or LLM training.

A GitHub Action for catalog submissions and pull-request classification. Jev answers policy questions; code applies the rules and updates a templated PR comment. Requires repository configuration and provider access.

A game agent that reads emulator memory and gives Jev legal options for navigation, menus and battles. The harness handles movement mechanics. Requires a legally obtained game copy and provider access; no ROM is included.

A Chromium T-Rex game with manual play and an optional Jev controller. Jev chooses jump, duck or keep running; browser code handles frame timing, collision geometry and execution. AI mode requires a TypeSafe key.

A pre-release library combining Jev-compatible text judgments with tabular model predictions. Uses your labeled rows and numeric columns alongside text-derived features. Bring both model backends; the API may change.

Entity recognition from natural-language type definitions. Code proposes text windows; Jev nominates and verifies candidates, then resolves boundaries and types. Outputs text offsets, probabilities and decision traces.

Evaluates agent traces with typed checks for tool use, grounding, quality and security. Supports Jev through several providers and other decision backends; requires configured provider access.

An experimental Chrome extension that asks Jev whether candidate page elements are ads, then highlights or removes them. A learning demo with false positives, not a tracking or malware blocker.

A Java client and Spring AI integration for Jev judgments, guardrails, RAG post-processing and tool selection. Includes runnable examples and typed request/response models; needs a TypeSafe key.

A Codex skill and Python CLI that recommends installed skills using description ranking and excerpt checks. Can return no suitable skill or uncertainty; it does not install or execute the recommendations.

A local PR reviewer that uses Jev to prioritize changes and presents natural-language explanations alongside code. Posts nothing to GitHub. Live analysis requires TypeSafe and OpenAI keys; demo explanations are prepared copy.