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). bash # 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.yml → persona.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.