DeepSeek Harness plugin

dsh-autonomous-research

自主研究 agent:给 AI agent 一个小而真实的 LLM 训练设置,让它过夜自主实验——改代码→固定 5 分钟训练→检查 val_bpb 是否改善→保留或丢弃→重复(约 12 实验/小时、一晚约 100 个);单文件修改、program.md 超轻量 skill。受 karpathy/autoresearch(94k MIT)启发。

Jump to install

Source facts

Repository
satan9394/dsh-autonomous-research
Latest update
Aug 20, 2026
Category
Workflow & Automation
GitHub stars
0
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/satan9394/dsh-autonomous-research
Plugin: dsh-autonomous-research
Author: satan9394

Check the source files

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

File explorer3 files
README.mdSource · read only

dsh-autonomous-research

DSH(DeepSeek Harness)技能插件:自主研究 agent

给 AI agent 一个小而真实的 LLM 训练设置,让它过夜自主实验:修改代码 → 固定 5 分钟训练 → 检查 val_bpb 是否改善 → 保留或丢弃 → 重复(约 12 实验/小时、一晚约 100 个);单文件修改(train.py)、program.md 超轻量 agent skill、固定时间预算让实验可比较、找最适当前平台的模型。受 karpathy/autoresearch(94k★)启发的中文原创精简版。

安装

dsh plugin add dsh-autonomous-research

触发方式

描述中包含"自主研究 / LLM 训练调参 / 过夜实验 / val_bpb / 自主实验循环 / 训练优化"等关键词时自动触发。

能力

  • 自主实验循环(改→训→判→保/弃)
  • 固定 5 分钟时间预算
  • val_bpb 词表无关比较
  • 单文件修改可审
  • program.md 超轻量 skill
  • 小平台调参指引

许可

MIT