In the “Everything Is a Plugin” ecosystem of DeepSeek Harness (DSH), tools for specific vertical domains are becoming increasingly rich. For developers working on empirical asset pricing and machine learning/deep learning research, data discovery and quality assessment are often the most time-consuming part. As a DSH plugin, Z Research · Data Stage aims to provide standardized data processing and evaluation capabilities for this workflow.

Plugin Focus

This is a DSH plugin maintained by Z-Asset, focusing on data discovery and quality assessment for asset pricing and machine learning/deep learning research.

Core Features

This plugin provides the following verified capabilities:

  • Data Processing: Supports data discovery and quality assessment.
  • Asset Pricing Research: Serves research workflows related to asset pricing.
  • Machine Learning/Deep Learning Research: Serves ML/DL-related research workflows.

Installation and Activation

First, ensure that DeepSeek Harness is installed. Install the plugin via the DSH CLI:

dsh plugin --profile <你的profile> add zresearch-data

Alternatively, it can also be installed directly via npm:

npm install zresearch-data

After installation, the plugin will load the corresponding skill on demand in a DSH session.

Typical Usage

After installation, trigger the corresponding functions directly with natural language in a DSH session:

  • Literature Review: Input “Help me do a literature review / find related papers”.
  • Data Processing: Input “Help me find data / evaluate a dataset”.
  • Model Training: Input “Run regression / train an ML model / cross-sectional return forecasting”.
  • Report Writing: Input “Write a paper / draft a section”.
  • Presentation Preparation: Input “Create a talk PPT / Beamer / job market talk”.

The model will automatically load the corresponding skill based on the task.

Technical Details and Domain

This plugin depends on the following peer dependencies:

  • @deepseek-ai/cordis
  • @deepseek-ai/dsh-skill

In terms of domain, it focuses on empirical asset pricing and machine learning/deep learning, covering scenarios such as factor models, cross-sectional return forecasting, GMM/SDF, and predictive regression. Its skill structure includes the skills/zresearch-data/ directory, which contains the main definition file SKILL.md as well as role definitions and domain calibration configuration files under the references/ directory.

Applicable Scenarios and Notes

This plugin is suitable for DSH users who need to process asset pricing and ML/DL data.

Notes:
1. The plugin runs with the permissions of the current DSH process. Check the source code and license (MIT) before installation.
2. Dependency versions must meet the requirements of @deepseek-ai/cordis and @deepseek-ai/dsh-skill.

Summary

Z Research · Data Stage is a data-processing helper tool focused on empirical asset pricing and machine learning research. Through standardized skill invocation, it streamlines the data discovery and quality assessment process and reduces manual operational costs.

For detailed documentation and source code, visit:
- GitHub repository
- SkillHub catalog