dsh-quant

🐳 dsh-quant — The Everything-Plugin Quant OS

📣 Announcement archive: 2026-09-01 X open-source launch copy

🌐 Site: https://dsh-quant-site.pages.dev · ✅ Listed in awesome-dsh-plugin (one-click install via dsh-market) AI-native & DSH-native quant toolkit for every quant aspect — 59 tools · 6 domains (data / alpha / ML / risk / execution / ecosystem) · one end-to-end PDAT→PET research pipeline. Methods open, secrets internal. 🧩 Core Philosophy: Everything is a Plugin (quant edition)

dsh's philosophy is everything is a plugin; dsh-quant brings it to quant — open-sourcing the internal five-team paradigm (PDAT → PAAT → PCPT → PRT → PET) as five pluggable modules: What's open is the paradigm: how modules compose, how contracts are defined (null alignment / no look-ahead / hand-computed tests), how results are validated — not the internal secrets You fill it in: product power = UI + strategies + data interfaces + DL/RL models + trading-system building, all self-assembled, all pluginized Infinite self-evolution: fill the framework with your modules → run paper/live → feed the ecosystem back — that's dsh-quant

Plugin call for proposals: Issue #27 (five modules × many plugins) — PDAT plugins, PET plugins, anything you can imagine 🐋 🤖 AI-Native Is Deliberate (design statement)

dsh-quant's primary consumer is the agent (the model), not the human — a deliberate choice from day one: Tool schemas are injected into the system prompt — every contract (args / outputs / alignment rules) is written from the model's perspective Equal-length null alignment — outputs match input length; leading window positions are null, so the model aligns by index and never pads Canonical JSON + render separation — machines read structure, humans read prose All isConcurrencySafe — pure functions, no shared state; agents can call all 59 tools in parallel without interference Skill layer — skill/quant-research lets the model load the workflow itself

Full statement: Issue #14 "AI-native is deliberate". 🐍 Why Almost No Python?

A common question: a quant project without .py files? Answer: 0 Python files, 21 TypeScript source files, zero runtime dependencies — deliberate: dsh-quant is a dsh plugin running inside the harness's Node runtime: same process as the agent, composable by the Loader, reversible registration (HMR-safe) — TypeScript is the only natural choice Where Python is needed (akshare / tushare / baostock), use the channel knowledge base (quant_data_guide, 16 channels): dsh ships shell / subprocess capabilities, so the agent decides whether to spawn Python — dsh-quant carries no runtime All numerical methods (indicators / backtests / options / bonds) are pure functions with hand-computed baselines: zero deps, offline-verifiable, npm test green anywhere

One goal: build the most usable AI-native quant repo 🐋

59 quant_* tools · 6 domains · 298 tests · zero runtime deps. Full positioning: pinned Issue #9. 🤖 For visiting agents

Agents landing on this repo: start at AGENTS.md (root-level, auto-read by Copilot / Claude Code / dsh), then the closed-loop example plugin/CASE_STUDY.md or Discussion #38, and the one-glance contract mcp/AGENT_GUIDE.md. Compatibility release status

The 0.91.1 release candidate includes DSH 0.2.1-rc.2 compatibility, with 0.1.0-rc.6 / 0.2.0-rc.2 / 0.2.1-alpha.3 coverage retained. npm was still at 0.90.0 when this candidate was prepared on 2026-10-18. Check the delivery record and npm view dsh-quant version before treating the fix as published. Original compatibility contribution: @hufeide (#136); user reports: @ziladan (#139 / #140).

The v0.91.1 tag is fixed to the reviewed source. Its first authenticated publisher attempt failed with npm E404, so the tag is not evidence of npm availability. See delivery attempt. Maintainers can manually run release acceptance with source=candidate to reproduce the Linux package, or source=registry after publication to verify four clean real-Loader consu