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dsh-verify

Workflow Updated 2026.08.27

Run the following command in DeepSeek Harness:

dsh plugin install 263311487-ux/dsh-verify

Paste the following prompt into your AI chat to install this plugin:

To install this plugin in DeepSeek Harness, run the command: dsh plugin install https://github.com/263311487-ux/dsh-verify

About this plugin

When an AI agent claims to have built a web app and declares it 'done,' can we truly trust its self-assessment? Traditionally, agents may rely on assumptions or static checks to validate outputs, but they often fail to simulate real user experiences in a browser—like clicking buttons, verifying style changes, or detecting console errors. dsh-verify addresses this credibility gap by acting as an independent quality gate that uses real browsers (such as Chromium, Firefox, or WebKit) to perform human-style checks, ensuring apps actually work as intended.

The core capability of this plugin lies in its deterministic verification: you simply write a JSON spec defining key interactions and expected outcomes, and dsh-verify automatically executes these steps in a browser, generating an HTML report with screenshots and diff images for clear pass/fail results. It supports multiple use cases, including serving as an MCP server for AI agents to self-verify during development, a CLI for manual or CI/CD pipeline checks, and integration into GitHub Actions for automated validation. Whether you're building frontend features or complex interactions, dsh-verify catches issues that agents might miss, such as missing CSS rules or JavaScript bugs.

dsh-verify is ideal for AI agent developers, teams using tools like DeepSeek Harness, and any engineer building web apps in CI/CD pipelines. If you're tired of agents 'grading their own homework' and want a reliable way to prove app quality, this plugin provides objective evidence. It avoids LLM judgment, instead letting the browser be the ultimate judge, helping you catch real-world defects before release to boost delivery credibility and user satisfaction.

Screenshots

Use Cases

  • Verify if AI-generated web apps function correctly.
  • Integrate automated browser checks in CI/CD pipelines.
  • Allow AI agents to self-verify output quality during development.

Best For

  • AI agent developers and test engineers.
  • Teams using tools like DeepSeek Harness.
  • Frontend engineers needing to ensure web app quality.