CHplus0/dsh-learning-mode

一个DeepSeek Harness(DSH)代理预设,边编码边教学——基于具体情景的讲解、苏格拉底式引导以及TODO(你)的实践空白,模仿Claude Code的学习输出风格。学习模式

项目介绍Project Overview

dsh-learning-mode 是 DeepSeek Harness 的智能体预设,以教学优先的方式协作编程:结合场景化讲解、引导式提问(先预测再验证)与 TODO(你) 实践留白,让你在动手中学。适用于希望边做边理解原理的用户;启动新会话时选择"学习模式"即可。需注意:安全关键、不可逆或正确性关键的步骤不可留空。

dsh-learning-mode is a DeepSeek Harness agent preset that teaches while coding. It combines scenario-grounded explanations, guided predict-then-verify questions, and TODO(你) practice blanks tied to the current task. Use it when you want to learn principles by doing rather than receiving finished code. Caveat: the preset never leaves blank any safety-critical, irreversible, or correctness-critical step.

或使用命令行安装(适合开发者)Or use CLI install (for developers)

命令行安装CLI Install

dsh plugin --profile web add dsh-learning-mode

CHplus0/dsh-learning-mode 加入你的 DSH 配置(web profile)即可启用。

READMEREADME

dsh-learning-mode

English | 中文

An agent preset for DeepSeek Harness (DSH) that teaches while coding, modeled on Claude Code's official Learning output style: explain concretely with usage scenarios, guide your thinking with questions, and leave explicit practice blanks for you to do by hand.

Learning output style (Claude Code): "Collaborative, learn-by-doing mode where Claude will not only share 'Insights' while coding, but also ask you to contribute small, strategic pieces of code yourself."

Three Pillars

Pillar Behavior
A · Concrete, scenario-grounded explanations Flexible, task-tied explanations: everyday analogy (boundaries marked when applicable) + scenario grounding (when/which/why results differ), used as needed; simple concepts get a sentence or two, complex ones get expanded. Depth layered (surface → medium → deep), deepen on demand; no re-teaching within a session
B · Guided thinking Question first: at conclusions you can reach yourself, ask one precise predict-then-verify question. When stuck, climb the hint ladder: L1 point at what to look at → L2 point at the principle → L3 reveal with explanation
C · Practice blanks Leave small, strategic pieces to you, marked TODO(你) (Claude Code's TODO(human)). Small, strategic, tied to what you're actually doing, self-verifiable; never blank safety-critical, irreversible, or correctness-critical steps

Interaction protocol: Teaching-first by default; "just do it / no time / asap" switches to direct mode; asks your familiarity level (beginner/intermediate/advanced) once at the start; ≥2 failed attempts downgrades to a guided reveal. Output language follows your input: Chinese in, Chinese out; English in, English out.

Examples

Teaching DeepSeek Harness's principles — the verbatim output of a real learning-mode session — a full teaching turn showing how concrete explanations, guided thinking, a context-tied TODO(你), and the one-time opening calibration work together. This file is human documentation and is never loaded by any skill: the learning-mode skill teaches only principles and forms (placeholder templates); concrete examples are invented at runtime from your current task, so fixed examples cannot degrade generalization. If you want to keep a permanent example, put it here — not in learning-mode/skills/.

Install

Requires DSH 0.1.0-rc.x (a deployment with profiles/ under ~/.dsh).

# Option 1: clone and copy
git clone https://github.com/CHplus0/dsh-learning-mode.git
cp -r dsh-learning-mode/learning-mode ~/.dsh/.agent-presets/

# Option 2: run the installer
bash dsh-learning-mode/install.sh

# Option 3: install the npm bundle (auto-installs the preset)
dsh plugin --profile web add dsh-learning-mode

Then open the DSH web UI, start a new session and pick 学习模式 (Learning Mode) — no restart needed.

Customization

  • Tone & identity: edit learning-mode/agent.cordis.ymlpersona.text.
  • Style details & phrasing templates: edit learning-mode/skills/learning-mode/SKILL.md.
  • Rename: edit only name in learning-mode/preset.yml (the directory name is the preset id, must match [a-z0-9][a-z0-9-]*; renaming requires renaming the directory too).

How it works

  • agent.cordis.yml is a full copy of the standard preset with two changes: the persona is replaced with the teaching identity (the three pillars, always in the system prompt), and skill-filesystem gains customSkillDirs pointing at this preset's bundled skills/ directory (the full guide loads on demand, not in the standing prompt). The toolset is identical to the standard coding agent (Shell, files, search, Skills, planning, goals, subagents, workflows).

License

MIT © 2026 CHplus0. The preset composition is adapted from the standard agent preset of deepseek-ai/deepseek-harness (MIT © 2026 DeepSeek); see LICENSE.

上一个 Prev dsh-jupyter 下一个 Next dsh-galgame-generator