DSH Wiki DSH Wiki
English ▾
English简体中文繁體中文日本語한국어ไทยEspañolالعربية
DEEPSEEK HARNESS · THE FULL ECOSYSTEM RECORD

Everything is a Plugin.

What this site is
DSH Wiki is the DeepSeek Harness ecosystem site built by ai798 Lab. dsh shot to 149,851 stars after going open source, and the plugins, tutorials, hands-on tests and arguments are scattered across GitHub, Reddit, X and a dozen outlets — this site keeps them in one place: follow the timeline to see how it blew up, follow the deploy guide to get it running, pick what to install from 12 featured plugins, then read what people who have actually used it are saying around the world. Every number and command was scraped first-hand, and each one links back to the source.
Quick Install → Tutorial
Official deepseek.com/harness deepseek-ai/deepseek-harness
149,851
GitHub stars on the official repo
30
Ecosystem plugins indexed
12
Featured plugin deep dives
68
Primary sources annotated
Live-scraped data
01 / TIMELINE

Timeline

Every step from launch to 149,851 stars — every plugin, comment, and data point pinned to the day it happened.
08.13

DeepSeek open-sources Harness v0.1 developer preview

The repo went public at 11:56 UTC; the official announcement tweet followed at 13:02 UTC: open-sourced under the MIT license for agent harness developers worldwide, powered by the Cordis meta-framework, with 'Everything is a Plugin' as the core idea. DeepSeek also released the Cordis design paper co-authored with Peking University, 'A Programming Paradigm for Spatiotemporal Composability'. The repo passed 20,000 stars in roughly an hour — compressing records once measured in days into minutes.
Announcement tweet engagement · 19.8k likes / 774 replies
Scraped directly from the Twitter syndication endpoint, collected 2026-08-18 (material 038)
Repository publication time · 2026-08-13 11:56 UTC
pasqualepillitteri.it report
First-hour star count · Passed 20,000 in about 1 hour; 22,000 at 1.5 hours
pasqualepillitteri.it report; KuCoin newsflash (relayed via material 020)
Source 1 Source 2 Source 3
08.13

V4-Pro GA ships the same day; API price hike set for August 17

Alongside Harness, DeepSeek-V4-Pro-0813 went GA: a 1M-token context window, up to 384K output, with Json Output / Tool Calls / Responses API support. The same announcement flagged a steep API price increase from August 17 plus a new peak/off-peak pricing scheme — 'the price butcher is done with bargain-bin prices' became the parallel storyline in Chinese media that day.
V4-Pro specs · 1M context / 384K max output
Reports from 搜狐 (Sohu) and 网易科技 (NetEase Tech)
Price change notice · V4-Pro peak-hour output 6 yuan -> 27 yuan per million tokens (+350%), effective 8-17
网易 (NetEase, 163.com) and 新浪财经 (Sina Finance) reports, 2026-08-13
Source 1 Source 2 Source 3
08.13

736 points on Hacker News: overseas developers put it on trial, day one

It topped the HN front page on launch day (736 points, 309 comments). The technical crowd endorsed the hot-swap, RAII-style plugin lifecycle design, with jbellis declaring 'the last mainstream model lab without a first-party harness just filled the gap'; skepticism centered on the thin README and the Node.js stack. The New Stack, Synced (Jiqizhixin), and other outlets in English and Chinese published the first wave of coverage the same day — the Synced piece was republished by at least 5 platforms.
HN traction · 736 points / 309 comments
Scraped directly from the HN Algolia API, collected 2026-08-18 (material 055)
Source 1 Source 2 Source 3
08.13

The ecosystem jumps the gun: plugins and lists created on launch day

The awesome-dsh-plugin curated list and the community desktop client DSH Desktop were both created on launch day; some 20 identically named 'awesome' repos popped up between Aug 11 and 14 in a name-squatting race — the 0xsline version was created 2 days before the official reveal, hinting the beta-test ecosystem had been mobilized early. The official repo opened Discussions but not Issues, and the first hot threads ('ship a standalone client + CLI sooner', 166 upvotes) sketched out the plugin demand map.
awesome name land-grab · 20 repos with awesome+dsh in the name, created mostly between 08-11 and 08-14
GitHub API search, collected 2026-08-18 (material 016)
Later size of projects created that day · awesome-dsh-plugin 7,572 star; DSH Desktop 11,626 star (as of 08-18)
GitHub, collected 2026-08-18 (materials 015, 009)
Source 1 Source 2 Source 3
08.14

Official Ollama support: run DSH locally with one command

At 22:30 UTC the day after launch, Ollama announced official DeepSeek Harness support: `ollama launch dsh` runs it fully locally, with the Ollama web search plugin preinstalled and a trajectory view for watching the agent work in the background. A top ecosystem player integrating within 48 hours — and the official on-ramp for running DSH locally and privately.
Tweet engagement · 1.0k likes / 38 replies
Scraped directly from the Twitter syndication endpoint, collected 2026-08-18 (material 041)
Source 1
08.14

Breakout day: 92,000 stars in 28 hours, and a wave of Chinese deep-dive reviews

Past 92,000 stars in 28 hours (per press coverage; the video title from Chinese YouTuber 零度解说 claimed '68,000 stars in a single day'). QbitAI's hands-on deep dive coined 'dsh is the Android of the agent era', revealing 100+ built-in official plugins and a reserved Plugin Store entry point. Videos from 零度解说, NeuralNine, AI超元域 and others landed in both languages, and DSH broke out of programmer circles into the broader tech audience.
28-hour star count · >92,000
pasqualepillitteri.it report
24-hour star count (figures disagree) · 68,000(estimated)
The figure used in the 零度解说 (Zero Degree Commentary) video title, which differs from the reported 12h~=50k / 28h~=92k figures; note the source whenever one is chosen
Official bundled plugins · 100+, with the Plugin Store already reserved
Hands-on article by 量子位 (QbitAI) (material 058)
零度解说 video views · 72,170 views (4 days)
Scraped directly with yt-dlp, collected 2026-08-18 (material 064)
Source 1 Source 2 Source 3
08.15

100,000 stars in 48 hours: record claims and the are-they-real fight

X blogger ℏεsam declared '100K in under 48 hours, GitHub's fastest-growing repo, faster than OpenClaw'; Jen Zhu offered a '114K in 3 days' figure the same day. A 369-upvote r/tech_x thread ignited a full-blown debate over whether the stars were genuine: 'star-farming bots have ruined GitHub' versus 'GitHub users are professional programmers'. Caveat: 'fastest in GitHub history' carries no official or authoritative third-party certification — cite it as 'media and community claims'.
48-hour star count · 100,000+
X post by ℏεsam (@Hesamation)
3-day figure · 114,000
X post by Jen Zhu (@jenzhuscott)
Precise value at about 2 days · 95,386 star / 8,826 fork
Flowtivity analysis article
Controversial post traction · 369 upvotes / 108 comments
arctic-shift archive (snapshot 08-17), material 023
Source 1 Source 2 Source 3
08.15

The V4-Pro 'rabbit hole': Minimal mode is the RL training environment

A hot r/DeepSeek thread translated a long post from the Chinese community: the V4-Pro API appears to hide multiple versions with different 'chain-of-thought fingerprints', and the strongest 'god-tier version' was dug out of DSH's Minimal mode. The key evidence: an August 10 commit in the official repo, 'fix(preset): align minimal agent with RL composition'. The top-voted conclusion — 'V4 Pro GA is overfit to the DSH minimal environment' — pushed 'the harness is the deciding variable in model performance' from anecdote to mechanism.
Post traction · 157 upvotes / 23 comments
arctic-shift archive (snapshot 08-16), material 031
Benchmark score comparison · Minimal 99/96 vs Standard 91
Community comparison experiment inside the thread (materials 031, 032)
Source 1
08.15

A mechanism-level community breakthrough: dsh-anchored-standard lifts the benchmark from 91 to 98/99

Community author xiaobright built a hybrid plugin on top of the 'rabbit hole' findings: the first request shows the model an environment nearly identical to Minimal, 'anchoring' it onto the reasoning track RL trained it for, then unlocks the full Standard toolset — lifting the benchmark score from 91 to 98/99, backed by a controlled experiment (the first request's tool schema is the decisive variable). Two days after open-sourcing, the community had produced a verifiable mechanism-level breakthrough — the first empirical payoff of 'Everything is a Plugin'.
Benchmark scores for four configurations · Standard 91 / PTC 92 / Minimal 99·96 / Anchored Standard 98·99
Comparison experiment inside the r/accelerate thread (material 032)
Post traction · 47 upvotes / 2 comments
arctic-shift archive (snapshot 08-17)
Source 1
08.16

Day 4: past 135,000 stars

Cross-checked across sources: 135,042 stars and 13,592 forks on day 4. For scale: DeepSeek's own R1 took 5.7 days to reach 20,000 stars, and the previous pure-speed record holder, Grok-1, took about 1.2 days. DSH covered the same distance in just over an hour.
Day-4 star count · 135,042 star / 13,592 fork (date estimated)
Cross-checked across the multiple sources in material 020; pasqualepillitteri.it: "passed 135,000 on day 4"
Reference points · R1 took 5.7 days to reach 20,000 star; Grok-1 about 1.2 days
pasqualepillitteri.it report
Source 1 Source 2
08.16

Third-party models and cache evidence: DSH isn't just for DeepSeek

An r/LocalLLaMA user ran Qwen 3.8 27b with DSH for 10 hours straight and called the results 'stunning', confirming that model-as-plugin generalizes; a follow-up thread — 'is the DSH cache hit rate really that magical?' — turned into a clearinghouse for hands-on plugin evidence; and the first plugin directory site, dshplugin.online, made Show HN. The ecosystem began shifting from spectating to reproducible testing.
Qwen hands-on post · 139 upvotes / 46 comments
arctic-shift archive, material 030
Cache follow-up thread · 14 upvotes / 29 comments
arctic-shift archive, material 033
Source 1 Source 2 Source 3
08.17

Official v0.1.0-rc.7: the Job Panel takes charge of Codex and Claude Code

The only visible release of the launch window (pre-release, 12:01): plugins can register their own settings cards, the Job Panel manages Codex and Claude Code sub-agent jobs in one place, MCP/ACP gains persistent image attachments, and fixes land for issues like persistent Bash latency in minimal mode. 'Managing rival harnesses as sub-agents' went from community reading to official feature.
release · v0.1.0-rc.7, 2026-08-17 12:01, Pre-release (original highlights in github.json)
Scraped directly from the GitHub releases page, 2026-08-18
Source 1
08.17

New API prices take effect: peak rates up more than 3x, community wishes for a rollback

The hike announced on Aug 13 kicked in: peak-hour output went from 2 to 9 yuan per million tokens on V4-Flash and 6 to 27 on V4-Pro (+350%), with cache-hit prices up as much as 1,100% by some counts; peak/off-peak pricing arrived too, with off-peak at half price. Discussions filled with 'roll back the pricing' wish threads and 'will Boss Liang cut us a deal?'; QbitAI's headline 'I forgive the price hike' became the Chinese community's mood in one line.
Peak-hour output price · V4-Flash 2->9 yuan, V4-Pro 6->27 yuan per million tokens (+350%)
Reports from 网易 (NetEase, 163.com) and 搜狐 (Sohu)
Largest reported increase · 1100% (cache-hit price: V4-Flash 0.02->0.10 yuan, V4-Pro 0.025->0.30 yuan)
新浪财经 (Sina Finance) report, 2026-08-17
Community reaction · Discussions #61 "roll back pricing" 30 upvotes, #32 "will Liang Wenfeng give us a discount" 28 upvotes
Scraped directly from GitHub Discussions, 2026-08-18
Source 1 Source 2 Source 3
08.17

The community's first 'must-install list' — and the first bad-plugin complaints

The new r/DeepSeekHarness subreddit produced its first curated index of plugins, skills, and MCPs; the same day, a complaint thread warned that 'one bad plugin can take down the whole plugin system', making single-point failure the first named weakness of the all-plugin architecture; and the trading-analysis plugin dsh-trading made Show HN. The ecosystem moved from celebration into list-building and fault-finding.
Post traction · Must-install list post 1 upvote, complaint post 1 upvote (cold start for a new board; traction is low, but these are the first of their kind in the launch window and were included for topic exclusivity)
arctic-shift archive, materials 036, 037
Source 1 Source 2 Source 3
08.18

150,000 stars in 5 days, 6,716 repos under the topic

First-hand data from the GitHub API: 149,856 stars, 15,364 forks, 627 watchers; the dsh-plugin topic now spans 6,716 repos, led by open-design at 88,304 stars, with big-company projects like Volcengine's OpenViking in the top 10. Later that day the repo page already read 151.3k. In 5 days, DSH grew from a single announcement tweet into a full plugin ecosystem spanning desktop clients, memory, vision, and design.
Official repository · 149,856 star / 15,364 fork / watch 627
First-hand collection via the GitHub API, 2026-08-18 (materials 020, 001)
Same-day figure from the page · 151.3k star / 15.6k fork / 638 watch
Scraped directly from the GitHub repo page, a supplementary capture on 2026-08-18 (later than the API collection)
Ecosystem size · topic dsh-plugin: 6,716 repos; top1 open-design 88,304 star
GitHub Search API, 2026-08-18 (materials 007, 008)
Source 1 Source 2 Source 3
02 / DEPLOY

Get It Running

From zero to a running instance in four steps. Every command checked line by line against the official README.
01

Install the CLI

One npx command and you're running — macOS, Linux, or Windows, Node 22.19+ is all it takes.
02

Connect a model

Drop in a DeepSeek API key, or point it at Ollama and use a model running on your own machine.
03

Launch

Work straight from the terminal — or run dsh web for a browser UI if the command line isn't your thing.
04

Install your first plugin

Pick one from the curated list and install it — from here on, everything is a plugin.
npx @deepseek-ai/dsh web pnpm dsh plugin --profile web add dsh-smooth-stream
Quick start →
Run instantly with npx, no install — the official default
From source →
Clone the repo, build with pnpm — hackable and moddable
Full tutorial →
From model config to your first plugin, one guide covers it all
03 / PLUGINS

Plugin Picks

12 plugins worth installing — each with install commands, usage notes, and real word of mouth.
dsh-anchored-standard 3,423 star

Minimal first, full firepower second.

A two-stage preset: it opens in minimal mode to cut the noise, then switches to the full standard toolset mid-session. Community controlled experiments lifted the benchmark score from 91 to 98. Note: the author has stopped active development.
Install takes more than one line — open the plugin page for the full commands →
Config / preset
open-design 88,304 star

Turn dsh into your design engine.

An open-source take on Claude Design, built as a local-first desktop app. Hook it up to dsh and text edits render into visuals in real time. The biggest project in the ecosystem.
od agent setup deepseek-harness
Copy
Design / desktop app
DeepSeek-Reasonix 34,683 star

The DeepSeek-native terminal coding agent.

Designed around prefix-cache stability, so it can grind through long-running tasks unattended. The npm TypeScript line is now legacy; main development has moved to Go.
npm i -g reasonix
Copy
Terminal agent / CLI
OpenViking 28,891 star

Volcengine's context database for agents.

Memory, knowledge RAG, and Skills managed under one roof, with L0/L1/L2 tiered retrieval to save tokens — and big-company backing.
pip install openviking --upgrade
Copy
Memory / storage
colleague-skill 23,139 star

Your departed coworker, digitally rehired.

Turns a predecessor's docs, coding style, and pet phrases into a Skill that works the way they did — 'digital life 1.0', and the most talked-about project in the whole ecosystem.
Install takes more than one line — open the plugin page for the full commands →
skill / knowledge cloning
EverOS 12,081 star

One memory, usable everywhere.

A portable memory layer: local-first, Markdown-native, one self-evolving memory shared across agent apps.
uv pip install everos
Copy
Memory / storage
awesome-dsh-plugin 7,572 star

Plugin hunting starts here.

A curated plugin directory with hand-verified source code — roughly 800+ plugins across 20 categories, plus dshmarket, its companion plugin marketplace.
Install takes more than one line — open the plugin page for the full commands →
Directory / list
dsh-web-ui 4,097 star

Give dsh a face.

The full Web UI plugin bundle: task boards, Git graphs, mobile remote control, a theme hub — if you want a GUI, install this.
dsh plugin --profile web add @linxin666/dsh-web-ui-all
Copy
UI
smooth-stream 21 star

A streaming-output plugin from the Chinese community.

Three presets tunable via cordis.patch.yml. The star count is modest; the buzz in Chinese-speaking circles is not.
pnpm dsh plugin --profile web add dsh-smooth-stream
Copy
Experience / output Editor's Pick
token-anxiety 0 star

Cost anxiety, relieved on the spot.

Real-time cost tracking, an Explain command that accounts for every token spent, and a price table you can sync with a single curl.
dsh plugin --profile web add dsh-token-anxiety
Copy
Cost / billing Editor's Pick
modlens 2,789 star

Eyes for text-only models.

The first vision plugin for dsh: paste in an image and get structured JSON evidence back, with failover across 10 engines.
npx -y @deepseek-ai/dsh plugin --profile web add @liustack/modlens@3.18.3
Copy
Vision / multimodal Editor's Pick
EchoBird 3,063 star

One-click installer and model switcher.

Manages installing and switching between Claude Code, Codex, dsh, and other CLIs in one place — the go-to for non-programmers.
curl -fsSL https://echobird.ai/install.sh | sh
Copy
Tools / installer
See all 12 featured plugins →
04 / GITHUB

GitHub Watch

Star counts, releases, and community discussion on the official repo.
STAR
08.1308.18 · 149,856
RELEASE
v0.1.0-rc.7
All releases
DISCUSSION

Please ship a standalone client and CLI sooner, plus an extension that supports vscode!

50
05 / RANKING

Plugin leaderboard

Ecosystem plugins ranked by stars, with loosely related topic-squatters filtered out. Star counts scraped 2026-08-18.
01
open-design Design
88,304
02
DeepSeek-Reasonix Terminal Agent / CLI
34,683
03
OpenViking Memory / Storage
28,891
04
colleague-skill skill
23,139
05
voyager Tools / Browser Enhancement
19,593
06
archify skill
13,847
07
EverOS Memory / Storage
12,081
08
learn-harness-engineering Tutorials
11,852
Full plugin leaderboard →
06 / INTEL

68 primary sources, every one ready for a close read

Official docs, in-depth reporting, community threads, and video tutorials — each annotated with a summary, key quotes, and data points. This is the raw material behind everything on this site.
Browse the archive →
07 / VOICES

What DSH users say

Real takes on DSH and its plugins from X and Reddit, each linked to the original post.
X @Hesamation · 2026-08-15
DeepSeek Harness is now the fastest growing GitHub repo, passing 100K stars in under 48 hours, even faster than OpenClaw. very positive community reaction: > unusually well designed architecture with tools, session log, agent loop, subagents, all being replaceable plugins > UI
2338 likes Source
X @eliebakouch · 2026-08-13
amazing release. it's a web UI with multiple harnesses inside it, you can spawn claude code and codex agent through their SDK "deepseek harness" supports different "modes" by default (which are harnesses): code mode with programmatic tool calling (in typescript), bash+edit
1250 likes Source
X @jenzhuscott · 2026-08-13
DeepSeek Harness v0.1's Cordis-powered design is probably one of the cleanest expressions of agent architecture I've seen: every capability - model adapters, tool registries, session logs, sandboxes, orchestration loops, and even the UI a is a 1st class plugin w typed services,
386 likes Source
Reddit u/stealthispost · 2026-08-15
**Anchored Standard** (xiaobright/dsh-anchored-standard) does a clever hybrid: 1. First model request: presents V4 Pro with essentially the same environment as Minimal... 2. As soon as it makes its first real tool call/reply, it unlocks the full Standard toolset... The author found that the tool schema on that first request appears to be the decisive variable.
47 upvotes Source
Reddit u/for4f · 2026-08-15
the anchored standard result is the one that got me. 98/99 with the full toolset handed back after the first call kills the 'fewer tools = fewer mistakes' explanation, which was the obvious alternative. so it really does come down to what the model sees at init. kinda fits the RL story though. train a model inside one specific scaffold and it'll behave best inside that scaffold, first message included.
4 upvotes Source
Reddit u/somerussianbear · 2026-08-16
I saw the dsh-anchored-standard plugin yesterday, the popularity of this thing and what it promised, and decided to give it a try on porting the approach to a Pi extension, cause I really like that harness and wouldn't like to have a harness just for DeepSeek. It works, I managed to replicate the whole thing. All thinking uses "We ...", as flagged by xiaobright as being the trace of a superior version of DeepSeek v4 Pro.
9 upvotes Source
What DSH users say →
DSH Wiki · The DSH Intel Hub · By ai798 Lab
DeepSeek Harness site GitHub
Live-scraped data