esengine/DeepSeek-Reasonix

It addresses the high token cost and latency of long-running AI coding sessions by optimizing for prefix-cache stability, which reduces repeated computation and cost. It also solves the rigidity of many AI agents by being fully config-driven and plugin-driven, allowing users to define providers, tools, and models in a TOML file without writing new code.

Developers can build a versatile AI coding assistant that integrates with any OpenAI-compatible API, run dual-model setups (executor + planner) for complex tasks, and extend functionality via MCP-compatible plugins. Real-world uses include automated code generation, refactoring, debugging, and repository-level analysis directly in the terminal. The ceiling is high: it can be tailored to any workflow, from simple autocomplete to multi-step autonomous coding tasks, with cost-efficient long sessions.