Dev & Engineering plugin-architecturenodejsweb-uicordisdsh

DeepSeek Harness (dsh)

An open-source agent harness from DeepSeek AI where everything is a plugin.

FollowAgents review · FARS-2.1
Use with care
65/ 100 5-point scale 3.3 / 5
1 2 3 4 5 6
1Trust17 / 29 · 2.9/5

Evidence shows: CI workflows explicitly set DSH_TELEMETRY_DISABLED=1 to prevent telemetry reporting, and web config rejects --host 0.0.0.0 to avoid remote code execution exposure, reflecting least privilege. User confirmation: no explicit user confirmation mechanism found, but config patches and hot reload may imply user actions. Data flow transparency: tests verify credentials not leaked to stdout/stderr, and config dump feature exists. Sensitive data handling: tests verify credential file permissions 0600 and Bearer token in request headers. Dependency security: uses pnpm lockfile and frozen install, but no vulnerability scanning evidence. External effects: tests verify network requests only to mock server, and telemetry disabled. Rollback: tests verify config reverts to default after patch removal. Source attribution: no explicit source attribution mechanism found, but third-party notices generation script exists. Deductions: user confirmation mechanism unclear, dependency vulnerability scanning evidence missing, source attribution unclear.

2Reliability9 / 14 · 3.2/5

Evidence shows: tests cover argument parsing, lifecycle, hot reload, etc., and CI has multiple platforms and node versions, indicating good self-consistency. Dependency availability: uses pnpm workspaces and lockfile, but not all dependencies' availability verified. Failure messages: tests verify error messages contain specific info, e.g., '--host 0.0.0.0 is intentionally not supported yet for safety'. Deductions: dependency availability not fully verified, failure message coverage limited.

3Adaptability12 / 18 · 3.3/5

Evidence shows: supports multiple profiles (web, headless, tui, etc.), and tests cover different scenarios, indicating clear audience and scenarios. Capability boundaries: web config rejects wildcard host, indicating boundary control. Trigger precision: argument parsing tests verify precise routing. Environment fit: CI covers Linux, Windows, macOS, and multiple Node versions. Deductions: no explicit audience documentation found, capability boundary description limited.

4Convention13 / 18 · 3.6/5

Evidence shows: README and bilingual translation pairing record exist, information architecture clear. Install notes: package.json has install scripts and postinstall. Naming stability: version 0.1.0-rc.5 indicates pre-release. Examples and FAQ: tests have examples, but no FAQ found. Known limitations: no explicit known limitations document found. License: MIT license clear. Versioning changelog: no CHANGELOG found, but version numbers exist. Maintenance responsibility: CI and release scripts indicate clear maintenance responsibility. Deductions: missing FAQ, known limitations, and CHANGELOG.

5Effectiveness9 / 13 · 3.5/5

Evidence shows: output usability: tests verify output format and content. Marginal value: plugin architecture and multiple profiles provide additional value. Cost benefit: CI and test coverage indicate reasonable investment. Deductions: no explicit performance or resource usage evaluation found.

6Verifiability5 / 8 · 3.1/5

Evidence shows: tests and CI provide verifiable evidence. Claim traceability: tests and documentation linked. Cross-source corroboration: CI and tests corroborate each other. Fact-inference separation: tests clearly distinguish expected and actual. Deductions: no independent third-party verification found.

Evidence confidence: Low Reviewed Aug 14, 2026 Reviewed revision 47f943859bef
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
Before you use it
  • No explicit user confirmation mechanism found, which may affect user informed consent for sensitive operations.
  • No vulnerability scanning evidence found for dependencies, recommend checking dependency vulnerabilities.
  • Missing FAQ, known limitations, and CHANGELOG, which may affect user understanding and maintenance.
Review evidence [1][2][3][4][5][6][7][8]
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What does this agent do, and when should you use it?

DeepSeek Harness (dsh) is an open-source agent harness developed by DeepSeek AI, built on a plugin-first architecture powered by Cordis, whose design is described in the paper "A Programming Paradigm for Spatiotemporal Composability". Currently in developer preview, it evolves rapidly with breaking changes. It can be run via npm or from source, providing a default Web UI at http://127.0.0.1:3080. The project is MIT-licensed and encourages community involvement through GitHub Discussions and Discord.

dsh provides a plugin-based runtime for building and interacting with agents. It starts a Web UI server with the command npx @deepseek-ai/dsh web (or pnpm dsh web from source). The Web UI allows users to manage and interact with agents through a browser interface. Its plugin system enables extensibility; community developers can publish plugins with the dsh-plugin topic for discoverability. It leverages Cordis for composability and supports a modular architecture where all components are plugins.

  1. Developers who want to build custom agents with a plugin-driven architecture and interact via a Web UI.
  2. Researchers interested in the Cordis design paradigm and seeking a flexible harness for experiments.
  3. Community members who want to publish and share agent plugins with a dedicated topic tag.
  4. Organizations that prefer self-hosted, open-source agent frameworks with permissive licensing and commercial viability.

What are this agent's strengths and limitations?

Pros
  • Plugin-first architecture powered by Cordis offers high extensibility and composability.
  • Web UI provides an accessible interface for interaction and management.
  • MIT license allows broad usage, modification, and commercial adoption.
Limitations
  • Developer preview status implies frequent breaking changes, unsuitable for production.
  • Documentation is limited; installation and usage rely primarily on the README and community support.
  • Requires Node.js (and pnpm for source builds), adding runtime dependencies.

How do you install or deploy this agent?

  1. Install Node.js. 2. Run npx @deepseek-ai/dsh web to start the Web UI.

How do you use this agent?

After installation, open http://127.0.0.1:3080 in a browser to use the Web UI. For source-based setup: git clone https://github.com/deepseek-ai/deepseek-harness.git && cd deepseek-harness && pnpm install && pnpm run build && pnpm dsh web.

FAQ

Is dsh production-ready?
No, it is in developer preview with breaking changes; avoid production use.
How can I extend dsh?
Build plugins and tag your repository with dsh-plugin for discoverability, following the contribution guide.
What are the licensing terms?
The project is MIT-licensed, permitting free use, modification, and commercial distribution.

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