DeepSeek Works from Russia Terminal

DeepSeek Harness

A layer on top of other agents, not a replacement for them.

Verified: Sep 12last change: Sep 20next price check: Dec 11

Price
your own key
License
MIT
Model
любой провайдер; свои DeepSeek V4.1 Flash и V4 Pro; вызывает Claude Code и Codex как субагентов
model under the hood
–
DeepSeek Harness: 'everything is a plugin'
DeepSeek Harness: 'everything is a plugin'

Facts with sources

  • Released August 13; within three weeks, about 165 plugins had piled up in the default install, and some of the published ones are malicious. Source (in Russian)
  • Deploying it on a clean server took the guide’s author about 25 minutes, with a second AI on hand to suggest commands. Source (in Russian)
  • Can call Claude Code and Codex as subagents. Source (in Russian)

Strengths

  • MIT licence; one npx command opens a browser dashboard on port 3080; any provider, including Bedrock, Vertex, Azure or a custom URL.
  • The trajectory log shows every call, the system prompt, reasoning and token spend per step, and a session can be exported for review.
  • Nate Herk, same Opus model: a YouTube analytics Excel in about 3 minutes vs 17 in Claude Code, a wiki search in 50 seconds vs 5+ minutes.
  • Reads AGENTS.md, CLAUDE.md and Claude skills with no changes; can call Claude Code and Codex as subagents.

Weaknesses

  • Officially a preview promising breaking changes: for Nate Herk creator mode kept reverting, compaction lost context, his mouse locked once.
  • DeepSeek's own models cannot see images: BridgeMind's V4 Pro failed a window-overlap bug given a screenshot, Grok 4.6 fixed it in one shot.
  • Unvetted plugins: a community audit found only 17 of 122 catalogued plugins install and 10 pass checks; AI RANEZ warns some carry malware.
  • Discussion 461 (Aug 13): an agent in full-access mode wiped a user's entire home directory (Edward Grishin).

Example from practice

An Excel report on a YouTube channel's analytics

Nate Herk sent the same vague prompt to DeepSeek Harness and Claude Code, both on Opus 5: find the recently pulled channel analytics and build an Excel sheet from them. The Harness came back in about 3 minutes, Claude Code in 17. The Harness version was shorter and easier to read: colour-coded views and engagement, top and bottom 10, monthly trend, tag analysis, though its charts had no labels. Claude Code's was wordier but deeper: all 467 videos, a top 50, more tabs and metrics. He would hand a client the Claude Code file; on a research report using his own skill, the Harness produced 4,400 words with 14 load-bearing sources against Claude Code's 5,000 words and 26.

source: Nate Herk | AI Automation, '100 Hours Testing Deepseek Harness vs. Claude Code. What You Need to Know.'

What reviewers say

Reviewer opinions on their own tasks and hardware, not measurements. Links go to the videos; transcripts live in docs/raw-data.

Who it is for

  • Engineer who already runs several agents and wants a layer over them

Models in this agent

Score is from our manager-task benchmark; models without a score are not measured yet.

DeepSeek V4 Pro (0813)DeepSeek V4 Pro 7.75DeepSeek V4 Flash 7.45DeepSeek V4.1 Flash

What changed

  • DeepSeek API: Chinese national holidays now count as discounted off-peak days, on top of weekends →
  • DeepSeek V4.1 Flash released: new architecture, 763B parameters, open weights, 1M context, native multimodality; a radically smaller KV cache makes long agent sessions cheaper and faster, and the API is another 50% cheaper off-peak →
  • DeepSeek V4 Flash Vision, an experimental multimodal version: reads screenshots and diagrams, files up to 64 MB →
  • DeepSeek Harness released: everything is a plugin, it calls Claude Code and Codex as sub-agents
  • DeepSeek V4 Flash 0731: the update beat V4 Pro on benchmarks with 10 times fewer active parameters, open weights, $0.14 per million tokens →
  • DeepSeek released V4 Pro and V4 Flash: analysing 10 thousand lines of code in Flash costs under a cent →

How to brief an agent like this

The four-line brief is the Foundation module: prompt structure, LLM agents and MCP, an AI policy for the team. It starts with the free open module.

Open in the workspace