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deepseek-reasonix

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esengine/deepseek-reasonix

DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.

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$ npm i -g reasonix

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Go

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MIT

License

2026-04-21

Created

2026-09-15

Last push

MIT-licensed, DeepSeek-native coding agent in a single Go binary — terminal, desktop, browser or editor via ACP. Standalone; the README describes no DeepSeek Harness (dsh) integration.

DSH integration

Ecosystem-related

Author-claimed

Safety audit

Unaudited

Last verified

2026-08-21

License

MIT

01What can it help you accomplish?

  • Run long autonomous coding tasks from the terminal with an agent you can leave running

    Code changes produced by a single local engine, guarded by plan mode, permissions, a workspace sandbox and per-turn checkpoints so runs stay readable and undoable

    Developers who want a DeepSeek-native coding agent for long unattended terminal sessions

  • Drive the same local Reasonix engine from your editor

    Native chat, editor context, tool-call approvals, model selection and workspace sessions in VS Code / VSCodium / Eclipse Theia via the `reasonix acp` backend

    Developers who prefer coding-agent sessions inside their editor instead of a separate terminal

02How to install into DeepSeek Harness

Prerequisites

  • npm on any supported platform, or Homebrew on macOS, for the prebuilt native binary path
  • Go 1.25+ only if building the CLI from source (desktop builds additionally need Node 24+, pnpm 10 and the Wails CLI)

Installation steps

  1. 01

    Install the CLI: `npm i -g reasonix` (any OS; pulls the prebuilt native binary) or `brew install esengine/reasonix/reasonix` (macOS)

    $ npm i -g reasonix

  2. 02

    Run `reasonix setup` to configure a provider and model

  3. 03

    Start an interactive session with `reasonix`, or run a one-off task with `reasonix run "implement the TODOs in main.go"`

Verify the integration

Not specified by the author

03DSH integration and capability boundaries

DSH integrationEcosystem-related

Standalone DeepSeek-native coding agent — the README describes no DeepSeek Harness (dsh) integration; ecosystem-level relation via the built-in DeepSeek model preset

  • Autonomous coding runs across four entry points

    a task or prompt from the terminal CLI/TUI, desktop app, browser, or an editor over ACPcode changes from one local engine, with plan mode, permissions, a workspace sandbox and per-turn checkpoints

    the agent writes and modifies project files in your workspace during a runmodel calls go to the configured provider endpoint over the network
  • Config-driven multi-model engine

    a `reasonix.toml` declaring providers, the agent, enabled tools and pluginsno hardcoded models — DeepSeek as a preset, any OpenAI-compatible endpoint as a config entry, optional executor + planner pair in separate cache-stable sessions

  • MCP servers and Extension Protocol plugins

    MCP servers or Extension Protocol v1 sidecars declared in the configextra tools, prompts and resources from MCP; sidecars can intercept runtime events, contribute Providers and structured UI, and ship versioned plugin packages

    extension sidecars can intercept runtime events
  • Cache-aware context maintenance

    a long-running session against prefix-cache-friendly endpointsa small stable environment summary injected at startup; stale tool output snipped/pruned before summary compaction

04Who is it for? When not to use it?

Good for

  • Developers who want a DeepSeek-native coding agent for long unattended terminal sessions
  • Developers who prefer coding-agent sessions inside their editor instead of a separate terminal

Not for

  • Reasonix does not work out of the box without a model provider: you must run `reasonix setup` to configure a provider and model before starting a session, and all generation traffic goes to that configured endpoint.

05Compatibility, maintenance and safety notes

  • Reasonix does not work out of the box without a model provider: you must run `reasonix setup` to configure a provider and model before starting a session, and all generation traffic goes to that configured endpoint.
  • Prebuilt binaries cover darwin/linux/windows × amd64/arm64, but building from source requires Go 1.25+ (pinned toolchain), and the desktop build additionally needs Node 24+, pnpm 10 and the Wails CLI.
  • The README describes no DeepSeek Harness (dsh) integration: Reasonix is a standalone agent, so there is no documented in-harness install path — its DeepSeek relation is that DeepSeek ships as a built-in model preset.
2026-04-212026-08-19desktop-v1.31.0

MIT · actively maintained (latest release desktop-v1.31.0, 2026-08-20)

06Frequently asked questions

How do I install DeepSeek Reasonix?

Run `npm i -g reasonix` (any OS; pulls the prebuilt native binary) or `brew install esengine/reasonix/reasonix` on macOS, then run `reasonix setup` to configure a provider and model. Prebuilt archives for darwin/linux/windows × amd64/arm64 with SHA256SUMS are on every GitHub release.

Does it integrate with DeepSeek Harness (dsh)?

The README describes no dsh integration. Reasonix is a standalone agent; its DeepSeek ecosystem relation is that DeepSeek ships as a built-in model preset, and any OpenAI-compatible endpoint can be added as a config entry in reasonix.toml.

Can I use it inside VS Code?

Yes — install the CLI first, then add the `SivanLiu.reasonix-agent` extension from the Visual Studio Marketplace or Open VSX Registry. It starts your local `reasonix acp` backend and adds native chat, editor context, tool-call approvals, model selection and workspace sessions.

How are models and tools configured?

Everything — providers, the agent, enabled tools and plugins — is declared in `reasonix.toml` with no hardcoded models. You can optionally run two models together (executor + planner) in separate cache-stable sessions, and MCP servers can contribute tools, prompts and resources.

What keeps long autonomous runs safe?

Plan mode, permissions, a workspace sandbox and per-turn checkpoints keep a long autonomous run something you can still read and undo. The whole engine is a self-contained static binary — nothing to install on the target machine beyond the binary itself.

08Data and sources

  • Author-claimedgithub.com43a4347fec94…

    DeepSeek ships as a preset; any OpenAI-compatible endpoint is a config entry, not new code.

  • Author-claimedgithub.com43a4347fec94…

    One local engine, four ways in — terminal, desktop app, browser, or your editor over ACP. Plan mode, permissions, a work…

This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-08-21. Found an error? Submit a correction.

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