vexjoy-agent GitHub avatar by notque

notque /

Routing & Cost Optimization

vexjoy-agent

An optional Jev routing path that matches VexJoy requests to specialist Agents, skills and workflows.

GitHub
42044
License: MITLanguage: PythonLast push: 9/19/2026#llm-routing-cost#mcp-integrations

What Jev Does in this Architecture

After deterministic routing guards, Jev judges the remaining candidates and required workflow components.

Key Architecture Benefit

Keeps repeatable routing rules and model-selected candidates in separate stages.

Review & Benchmark Note: Forced routing and unavailable-provider paths exist; not every dispatch is a Jev decision. Not run here.
Clone Repository
git clone https://github.com/notque/vexjoy-agent.git

Inspect on GitHub

Check out the upstream repository README, issues, and commit log.

notque/vexjoy-agent

Architecture Category

Routing & Cost Optimization

Complexity-based request routing to tier generative models and optimize token spend.

View all in this category →

Related Projects in Routing & Cost Optimization

53
Routing & Cost OptimizationMITPython

Uses Jev to classify each Codex turn, then applies local rules to choose the model, reasoning effort, and speed mode.

What Jev does here

Classifies task difficulty and reasoning needs before local policy selects a model configuration.

Keeps routing policy and decision logs local for inspection and tuning.

#llm-routing-cost#coding-agents
53 evidence links
Inspect details
jev-research repository icon by sherajdev

sherajdev

jev-research

1
Routing & Cost OptimizationMITTypeScript

A Jev and Herdr integration guide with a prototype for routing tasks to different Agents.

What Jev does here

Uses task and repository state to choose an executor and assess risk and dispatch readiness.

Provides a readable, editable example of multi-Agent task routing.

#llm-routing-cost#typed-decisions
2 evidence links
Inspect details
jev-demo repository icon by minghanminghan

minghanminghan

jev-demo

0
Routing & Cost OptimizationMITTypeScript

A customer-service routing demo that batches Jev questions before following the resulting route.

What Jev does here

Assesses classification levels, human-handoff intent and frustration, with low-confidence escalation.

Combines routing and human handoff while leaving response generation to the application.

#domain-workflows#classification-ranking
4 evidence links
Inspect details