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Automated security scan — not a certification.
Agent-native trading terminal built on DeepSeek Harness. Crypto, US, CN and HK in one three-column GUI, 19+ hot-swappable connectors, dry-run by default with human approval on every live order. BYOK, no data redistribution.
# Add to your Claude Code skills
git clone https://github.com/zhu1090093659/dsh-tradingLast scanned: 9/4/2026
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"status": "PASSED",
"scannedAt": "2026-09-04T08:43:40.115Z",
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}See how dsh-trading compares with popular alternatives.
dsh-trading is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by zhu1090093659. Agent-native trading terminal built on DeepSeek Harness. Crypto, US, CN and HK in one three-column GUI, 19+ hot-swappable connectors, dry-run by default with human approval on every live order. BYOK, no data redistribution. It has 269 GitHub stars.
Yes. dsh-trading passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/zhu1090093659/dsh-trading" and add it to your Claude Code skills directory (see the Installation section above).
dsh-trading is primarily written in TypeScript. It is open-source under zhu1090093659 on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh dsh-trading against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
Current Status & Handoff / 当前状态与交接：See docs/current-state.md (accepted milestones, fail-closed invariants, documentation map).
English | 简体中文
dsh-trading is an open-source, agent-native AI trading terminal and quantitative investment research platform built on DeepSeek Harness (DSH) and the Cordis microkernel. It unifies Cryptocurrency (Binance, OKX, Bybit, CCXT), US Equities (Alpaca, Interactive Brokers, Yahoo Finance), China A-Shares (MiniQMT, Eastmoney, AkShare, Tushare), Hong Kong Stocks (Longbridge, Futu, Tiger), and Chinese Commodity Futures into a single modular workspace.
Combining TradingView Lightweight Charts v5, role-based multi-agent teams (Master, Researcher, Trader, Risk Reviewer), built-in strategy backtesting, and a zero-trust dual-track human approval gate, dsh-trading bridges the gap between deep AI reasoning and disciplined trading execution.
Quick start · Key features · Why dsh-trading · Supported markets · Agent architecture · FAQ · Documentation
Your next trading terminal can also be your AI agent. No chumps for the slaughter, just everyday traders.
master lead, instrument-researcher, trader, risk-reviewer) that autonomously queries market data tools, performs financial statement analysis, drafts trade plans, and stresses risk scenarios.strategy_backtest, author custom technical indicators, and evaluate historical performance across market cycles.First, a question for you:
Of the money you've lost trading, how much of it was lost before you had truly thought it through?
You chase a rally and become the exit liquidity. You buy the dip, and it keeps dipping. You cut the loss, and it bounces the moment you're out; you hold, and it grinds you into the deep red. (Veterans don't always dodge these either.)
Where does the problem lie? Not in luck. In discipline.
The market opens every day, and bulls and bears fight it out every day. The most dependable weapon a retail trader holds was never better information — it's discipline. A seasoned hunter waits nine-tenths of the time and strikes in the remaining tenth; most traders do the exact opposite — nine-tenths acting, one-tenth regretting.
That is why dsh-trading exists: an agent-native trading terminal built on DeepSeek Harness (DSH). A professional trading workflow, paired with an AI agent in sync with the market: quotes, news, and capital flow are all in its view; research follows institutional-grade playbooks; and before a real order goes out, every single one passes an approval gate that only your hand can click.
Crypto, US equities, China A-shares, Hong Kong stocks. One terminal. One agent. Nineteen-plus connectors. Zero vendor lock-in — every key stays on your machine.
| Dimension | Traditional Trading Terminals (TradingView / Broker Apps) | Generic AI Chatbots (ChatGPT / Copilot sidebars) | dsh-trading (Agent-Native Terminal) |
|---|---|---|---|
| Multi-Market Scope | Fragmented accounts across different apps | Text-only dialogue; no live market feeds | Single unified watchlist & dock: Crypto, US, CN, HK, Futures |
| Real-Time Market Depth | Expensive subscriptions; walled gardens | Hallucinations; zero tick data or order books | Live L2 order book, tick-by-tick trades, crypto funding rates & open interest |
| Terminal Integration | None or simple external alerts | Chatbox glued next to chart; manual copy-paste | First-class terminal citizen: AI directly drives native quote tools & code analysis |
| Multi-Agent Architecture | None | Single prompt / single model | Hierarchical team: Master (Lead) + Researcher + Quant Trader + Risk Reviewer |
| Investment Research | Manual reading across disparate websites | Generic web-search summaries | Built-in institutional skills: Market risk checklists, 5-step crypto framework, valuation playbooks |
| Strategy & Backtesting | Proprietary scripting (Pine Script) in silos | Cannot run code on real market feeds | Native strategy_backtest engine & indicator authoring inside the workspace |
| Execution Safety | Manual clicks or opaque black-box algos | Dangerous unmonitored execution or none | Dual-track gate: Dry-run by default, human approval for live orders, Ed25519 authority |
| Privacy & Credentials | Keys stored on third-party cloud servers | Prompts & data sent to external cloud AI | 100% BYOK stored locally on your machine, zero data redistribution |
What do most "AI trading tools" look like? A chat box glued to the side of the chart.
Glued on, not grown in.
dsh-trading turns that relationship upside down: the agent is a first-class citizen of the terminal, and the terminal is the agent's body. Four things separate it from every chatbot you've used:
Quotes, news, capital flow — the agent has it all. Live quotes, the current candle, the chart series' time range with a fetch locator (so the agent pulls the same routed data itself and analyzes it in code), the computed readings of your active indicators, derivatives snapshots, plus announcements, news and a bounded fundamentals summary — all native tools the agent drives for the symbol you're watching. Missing sources are explicit; the agent is guided to verify original disclosures and fill gaps with native research tools. No more screenshot-copy-paste ritual.
The agent can trade, but the gate is in your hands. Market data, order books, derivatives positioning, news, and order placement are all native tools. Yet every order defaults to dry-run simulation; live routing requires an explicit liveTrading: true opt-in, and then each order still passes through interactive human approval. In headless environments it fails closed. One rule: no move without the gate. Nothing executes behind your back.
The agent trained for this. Domain knowledge ships as bundled skills, not model improvisation: pre-trade risk checklists for every market (crypto · US · CN · HK), a five-step crypto instrument analysis framework, a full company analysis playbook, and a trading journal discipline that dual-tracks "what the agent did" versus "what you did" — append-only and auditable.
The risk checklist runs before every entry — a discipline most veterans never sustain in ten years (usually undone by "just this once").
master (大师) is the all-capable multi-agent team lead: it grounds every trade question in the unified holdings ledger (holdings_list / holdings_stage) and per-ma