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CZ-ZL/duo#dsh-plugin

DSH plugin for bounded agent evaluation: compare an original with candidate prompt or supported configuration changes against user-supplied checks, record evidence and costs, and leave adoption to the user.

Stars ★ 0 Category Development & Runtime Listed 2026-09-18

Install

Inside DeepSeek Harness, with dsh-market

dsh plugin --profile web add dshmarket

Or from the command line

dsh plugin --profile web add github:CZ-ZL/duo#path:/dsh-plugin

Installing runs third-party code with your own permissions — it can read your files, use your credentials and reach the network. Review the source first, and pin a commit (github:owner/repo#sha) when you can.

README

English · 简体中文

DUO lets a DSH Agent evaluate an original prompt or supported component, try candidate changes against supplied tests, and return the changes, decisions and costs.

Start here: install → free check or real task → saved report

The Quickstart includes every command, the supplied task/evaluator and the owner-provided model configuration. An independent Caller has completed the real starter through this public guide; the original and candidate tied, so the original was retained. The local path checks product operation without model calls.

Developer preview: Linux / Node24+, tested DSH0.1.2-rc.1 / Cordis4.0.2. Version 0.6.3 is an unreleased source preview; the Quickstart packages its public source into an installable tarball. Previous released builds have versioned GitHub assets. Do not install the repository root or assume an npm release. Installation may fetch dependencies; it does not configure a model account or authorize experiments.

The default bundle offers preparation until compatible work providers are attached. The shipped starter supplies its own composition. Built-in model providers support persona/prompt; other Targets require matching providers. No candidate is automatically adopted. DUO inner costs exclude Calling Agent inference and local resources. Python/YAML compatibility remains behind /legacy; native use needs no Python.

Content from the project README on GitHub ↗

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