DeepSeek Harness plugin

dsh-quant-workspace

Self-contained quant workspace for DeepSeek Harness: bundled Python engine (Yahoo data) with pluggable strategies — single-ticker signal card / backtest / review tools.

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Source facts

Repository
AllenCX/dsh-quant-workspace
Latest update
Aug 14, 2026
Category
Tools & Capabilities
GitHub stars
1
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/AllenCX/dsh-quant-workspace
Plugin: dsh-quant-workspace
Author: AllenCX

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer4 files
README.mdSource · read only
README language

dsh-quant-workspace

English | 中文

A self-contained quant research workspace for DeepSeek Harness. It ships a Python engine inside the package — fetch Yahoo Finance daily data, backtest rule-based strategies, and generate interactive visual reports, all from chat.

> ⚠️ Not investment advice. The workspace surfaces rule state and evidence; decisions are > always yours. It never places orders and never changes positions.

Features

  • Data — Yahoo Finance daily bars (2 years by default), with OHLCV + indicator export.
  • Backtesting — per-trade table, total return, max drawdown, win rate, average hold, and a

buy-and-hold baseline.

  • Visual reports — self-contained interactive HTML charts: candlesticks with bands and

entry/exit markers, volume, %B, and an equity curve. Zoom (anchored at the cursor), pan, crosshair, and a red-up/green-down toggle — no dependencies, open in any browser.

  • Strategy registry — save strategies you have researched and reuse them by id.
  • Read-only by design — no orders, no position changes, no market-data keys.

Requirements

  • A DeepSeek Harness installation (web profile) with pnpm.
  • uv (runs the bundled Python engine; first use syncs python/.venv).
  • Internet access for Yahoo Finance data.

Install

> Installation status: not yet published to npm. Until then, install from the git spec > (dsh plugin --profile web add github:AllenCX/dsh-quant-workspace) or use the dev overlay below.

dsh plugin --profile web add dsh-quant-workspace

All configuration is optional. Example user patch ($DSH_HOME/profiles/web/cordis.patch.yml):

- id: quant-workspace
  config:
    ledgerPath: 'C:\path\to\trade_log.csv'   # optional: track your real positions
    reportsDir: 'C:\path\to\reports'          # optional: where visual reports go
OptionDefaultMeaning
ledgerPath(none)Position ledger CSV (date,ticker,action,price; FIFO). Positions are only tracked from this file.
reportsDir$DSH_HOME/dsh-quant-workspace/reportsDirectory for visual report artifacts (HTML charts) and state exports.
registryPath$DSH_HOME/dsh-quant-workspace/strategies.jsonStrategy registry JSON file.
defaultRule(none)Default rule family used when a call does not specify one.
timeoutMs180000Foreground timeout per tool call.
pythonCommanduv run --project <package>/python dsh-quantOverride for running the bundled engine CLI (e.g. a pre-built venv).

Dev / local overlay

pnpm dsh web --patch ./dev.patch.yml

Quick start

In a Harness session:

  • "Give me today's signal card for TSLA" — single_ticker, mode daily.
  • "Backtest META and generate a chart" — single_ticker, mode backtest, chart: true.
  • "Compare the review health check for TSLA" — single_ticker, mode review.

A call runs exactly one rule: an example rule family, a registered strategy id, or the configured defaultRule when neither is given. Without any of these, the workspace reports that no strategy is selected.

Tools

single_ticker

  • ticker (required) — symbol, e.g. TSLA. Uppercased automatically; only letters, digits, dot and dash.
  • mode (default daily) — daily signal card · backtest with per-trade table · review health check.
  • rule — an example rule family (currently bollinger_mean_reversion).
  • strategy — id of a strategy in the workspace registry.
  • chart (default false) — also write an interactive HTML report and the state CSV under reportsDir;

the artifact paths are included in the output.

Strategy registry

After research, save a strategy and reuse it by id:

dsh-quant strategy register --id tsla_dip --family bollinger_mean_reversion --bollinger-window 30 --note 'dip strategy after Aug-2026 research'
dsh-quant strategy list
dsh-quant strategy remove --id tsla_dip

Example rule

The bundled engine ships one example rule so the workspace works out of the box: Bollinger mean-reversion on daily bars — enter when %B <= 0, exit when %B >= 1 (Bollinger 20, 2σ, same-bar close fills, no transaction costs in v1). Rule parameters are CLI options, and more rule families (MA cross, Donchian, RSI, trend filters) are on the roadmap.

CLI reference

dsh-quant single-ticker --ticker <T> --mode <daily|backtest|review> (--rule <family> | --strategy <id>) [--ledger <path>] [--chart <dir>] [--export-state <dir>] [--registry <path>] [--data-file <csv>]
dsh-quant strategy register|list|remove [options]
  • Exit 0 with plain-text report on success; exit 1 when data cannot be loaded; exit 2 for invalid invocation.
  • --data-file reads a local OHLCV CSV instead of the network (used by the tests).

Development

pnpm install && pnpm run typecheck && pnpm run test && pnpm run build   # TS shell
cd python && uv run --project . pytest tests -q                          # bundled engine

License

MIT