DeepSeek Harness

What is the DeepSeek Harness?

It is the program that wraps a DeepSeek model so the model can do real work: read files, run commands, keep a plan, and stop to ask you first. DeepSeek released its own one, called dsh, as open source.

Agent=Model+Harness
Everything on this page, as a 96-second video. Captions are built in, so no sound is needed. Skip the reading if you like.

The model is the engine. The harness is the car.

model alone

Smart, but it has no hands

  • Gets text, returns text.
  • Cannot open your files or run anything.
  • Forgets everything when the call ends.
  • Has no brakes. Nothing stops a bad action.
model + harness

An agent that can finish a job

  • Tools give it hands: read, edit, run.
  • A loop lets it act, look at the result, and act again.
  • Sessions and plans give it memory.
  • Permissions are the brakes. Risky steps wait for you.

The same model can do much better or worse depending on the harness around it, the way one engine performs differently in different cars. That is why benchmark reports say which harness they used.

The agent loop, one step at a time

Example task: "Login tests fail. Fix them." Watch the harness pass work between you, the model, and the tools until the job is done.

Agent loop

You give a task

round 0
you → harness
Login tests fail. Fix them.

The harness receives your message. Nothing has happened yet.

Eight parts of any harness

Loop

Calls the model, runs what it asks for, feeds the result back, repeats.

Tools

Read file, edit file, run command, call an API or MCP server.

Context

Picks what fits in the model's window each turn and shrinks old parts.

Prompt

System rules and skills that shape how the model behaves.

Memory

Sessions, plans and saved state so work can resume later.

Permissions

A policy says which actions need your approval first.

Sandbox

Keeps commands the agent runs away from the rest of your machine.

Checks

Tests and linters that tell the agent whether it actually succeeded.

DeepSeek Harness, dsh

Made by
DeepSeek AI. Repo: deepseek-ai/deepseek-harness
License
MIT, open source
Status
Developer preview. The README warns of compatibility-breaking changes.
Released
Aug 13, 2026, with DeepSeek V4 Pro · one secondary source
Design
"Everything is a plugin", built on the Cordis plugin framework
You use it
Through a local Web UI in your browser, at 127.0.0.1:3080. There is also a Python SDK.
Agent can
Read and edit files in a workspace you pick, run commands, delegate work, and keep a plan
Brakes
Asks your approval before actions that the permission policy marks
Models
DeepSeek by default; other providers and OpenAI-compatible endpoints can be configured
Extras
Memory MCP, plugin markets, GitHub review sessions, session reminders
Everything is a plugin Cordiscore

Illustration. The README only says "everything is a plugin". The labels are capabilities named in DeepSeek's docs, not a confirmed list of built-in plugins.

Two things people mean by "DeepSeek harness"

most likely · high confidence

DeepSeek's own harness, dsh

The product above. DeepSeek built both the engine and the car.

loose use · medium confidence

A DeepSeek model inside someone else's harness

The harness stays the same and only the engine changes. DeepSeek's docs list these as supported:

Claude CodeCodexOpenCodeOpenClawHermesQoder

Agent harness vs eval harness

"Harness" also means the test rig used to score models. Different job, same word.

Agent harnessEval harness
JobLets a model act on real workMeasures a model on fixed tasks
Changes the score?Yes. It is part of what gets tested.No. It is the measuring tape.
Examplesdsh, Claude Code, Codex CLI, Terminuslm-evaluation-harness, SWE-bench grader, Terminal-Bench

Real example from the DeepSeek-V3.1 model card: SWE-bench Verified 66.0 was run in DeepSeek's "internal code agent framework", and Terminal-bench 31.3 in the Terminus 1 framework. Each score belongs to the model and the harness together.

Not proven yet

Sources

  1. github.com/deepseek-ai/deepseek-harness (README)
  2. DeepSeek Harness quickstart guide
  3. DeepSeek API docs: coding agents
  4. DeepSeek API docs: thinking mode
  5. DeepSeek-V3.1 model card
  6. Forklog: launch report (secondary)
  7. LangChain: the anatomy of an agent harness
  8. Anthropic: effective harnesses for long-running agents
  9. EleutherAI lm-evaluation-harness
  10. Terminal-Bench