Model routing with decision models

Pi extension for four-tier model routing with an optional classifier advisor (formerly Jev/Clef-specific, now any Pi classifier).

Adaptive thinking-level router for Pi: Jev or local rules pick low/medium/high/xhigh at task start, on reasoning failures and when stable.

Pi extension that classifies each request with Jev and routes it to one of three configured models, with doctor checks and shadow mode.

Pi-based coding agent where Jev gates every tool call, picks the model tier, checks 'done' claims and trims tool output.

Claude Code plugin where a local Decider model on your Mac picks the model and effort level for each subagent task.

Host-agnostic routing layer that picks model, effort and provider per round for coding harnesses from trajectory evidence.

Claude Code mod where Jev judges each message's /effort level and offers a one-key switch for that turn.

Local router for Claude Code and Codex that has Jev assess each new task, then pins a policy-chosen model and effort for the conversation.

Policy-driven router that sends each LLM request to the cheapest capable model tier, escalating when Jev finds a reason.

Prompt router for Claude Code, Codex and Antigravity that picks model, effort, skill and language per request via Jev.

Rust five-tier cascade router that sends prompts to Jev or an LLM, escalating only ambiguous requests.

Open-source AI coding agent with memory and specialist agents; the list notes an optional Jev dispatch classifier.

Preview router for macOS Codex where Jev picks the GPT model and reasoning effort for each request through an isolated profile.

CLI that filters coding-agent subscriptions by quota and policy, then asks TypeSafe to rank the rest and pick a reasoning effort.

Patched Codex CLI where Jev reads task context mid-run and picks the next reasoning effort level and how long it should last.

Experimental Paseo plugin where Jev, local Laya or OpenAI Decisions classifies each message and routes it to a provider/model preset.

Cost-, cache- and quota-aware LLM router that classifies each turn with a Jev-class model, prices every route, and checks cheap answers.

Effortlane: local router for native Codex on macOS that uses Jev to recommend model and reasoning effort per turn, with a Shadow mode first.

OpenAI-compatible local server pairing a small llama.cpp model for generation with Jev for the closed decisions.

Decision sidecar and Copilot CLI pre-turn hook that mimics Jev choice, noul and score using Azure Foundry Cohere Rerank.

Home Assistant conversation agent where Jev classifies an utterance and either calls a light, climate or cover service or hands off to Grok.

Hermes Agent tool plugin giving bounded Jev judgments and an explicit model recommendation via TypeSafe, Cloudflare or OpenRouter.

Experimental Hermes plugin returning routing plans: Jev rates task complexity, deterministic policy picks the cheapest eligible model.

Local proxy for Claude Code that uses Jev to pick model and effort per message, routing subagents but guarding the cached main chat.

Prototype per-call model router for Codex where Jev picks the GPT model and reasoning effort for each call via a local Responses proxy.

Six side-by-side demos where Jev makes the decision, Claude or Kimi writes the words, and code owns control flow.

Python agent development kit for building System One pipelines with Jev for guardrails, routing and PR triage.

Beginner manual, video script and three small examples for building an agent harness with Jev via langchain-typesafe.

LangChain notebook of practical Jev examples: ticket triage, model routing, reply guardrails, tool selection and finance-inbox fraud checks.

Local Anthropic-compatible proxy where Jev scores each Claude Code turn and simple work is routed to cheap or free models.