dsh-teacher ๐งโ๐ซ
> A DeepSeek Harness plugin that turns the agent > into a teacher โ never answers, always asks.
Give it a markdown file of questions. It leads you to the answers with the Socratic method, keeps a quiet ledger of the gaps it notices in your reasoning, and retests those gaps on-demand on a spaced-repetition schedule.
The loop
questions.md โโโถ /teach questions.md
โ LLM parse / tolerant parser
โผ
SQLite question store (courses + questions + quiz runs)
โ /quiz โ ๐ LLM-free quiz popup (MCQ / free-text)
โผ
answers โโโถ POST /dsh-teacher/quiz/submit (run stored)
โ "Quiz finished (run N)" โ LLM analysis
โผ
grade each answer (vs hidden keys) โโโถ gaps โ Socratic walk
โ gap ledger (persists across sessions, SQLite)
โ you: "/retest" (on-demand, anytime)
โผ
"Explain rebase to me." โโโถ graded, rescheduled (FSRS-5)Status
v0.3.0 โ core + Web client + SQLite question store + LLM-free quiz popup; tests passing (83/83).
| Milestone | Status |
|---|---|
| M0 Scaffold (bundle patch, plugin row, zero-build JS) | โ |
| M1 Core Socratic loop (curriculum parser, policy section, 5 tools) | โ |
| M2 Gap ledger + persistence (SQLite + JSON fallback, session events) | โ |
| M3 FSRS-5 spaced retest (official test vector pinned) | โ |
| M4 Web client (quiz cards, gaps button + panel, gap projection) | โ |
| M5 Publish (dsh-plugin topic โ, awesome lists, live e2e) | โ |
| M6 SQLite question store (courses/questions/quiz runs) | โ |
M7 LLM-free quiz popup (MCQ + free-text, POST /dsh-teacher/quiz/submit) | โ |
M8 Post-quiz LLM analysis + Socratic walk (analyze_quiz) | โ |
Design decisions are in [docs/PLAN.md](docs/PLAN.md) (ยง10 = the v0.3 redesign).
Web client
Once the plugin is installed and the web profile restarted, the browser bundle (lib/client.js, registered via dsh.client) adds:
- Quiz cards โ custom
tool.call.toolviewcards fornext_question,
grade_answer, note_gap, hint, and retest (question prompt, verdict color-coded by outcome, gap chips by kind).
- ๐งโ๐ซ gaps button โ in the session header action row, shows a due-count badge
and opens the gap panel.
- Gap panel โ floating overlay listing this session's gaps (kind, topic,
due/โ mastered), fed by the teacherGaps session projection (same seam dsh-usage-plugin uses). The durable cross-session ledger stays in /gaps and /retest.
- ๐ quiz popup โ the LLM-free quiz: questions come from the
teacherQuiz
session projection (loaded from the SQLite store, no AI involved); each question shows clickable multiple-choice options when present, else a free-text box, with a ๐ก hint toggle. Finish submits your answers to the plugin (POST /dsh-teacher/quiz/submit), then the teacher's LLM analysis grades them, records gaps, and walks you through the misses Socratically. Open it from the header button or /quiz.
Install
Requires DSH rc.6+ and Node โฅ 22.5 (uses built-in node:sqlite).
dsh plugin --profile web add "github:Yihong89/dsh-teacher"
# restart dsh --profile webUsage
# questions.md โ answer keys live in HTML comments; the teacher grades
# against them internally and never shows them to you.
---
title: Networking review
---
## Q1: What happens when TCP handshake fails?
<!-- answer: SYN gets no SYN-ACK; the client retries then times out -->
### hints
<!-- hint 1: Think about the three-way handshake. -->| Command | What it does |
|---|---|
/teach questions.md | Load the question set into the SQLite store and enter teacher mode (does not start teaching โ say "start", "quiz me", or ask about a topic) |
/teach on / /teach off | Toggle teacher mode (mode is session state, survives resume) |
/quiz | Open the LLM-free quiz popup over the whole bank (MCQ / free-text); finishing it hands the results to the teacher's LLM analysis and the Socratic walk over the misses |
/gaps | Show the gap ledger for this course |
/retest | Surface due gaps for an on-demand drill (FSRS-5 schedule) |
/summary | End-of-session knowledge-gap & misconception summary |
Teacher behavior (model tools)
next_questionโ pulls one question at a time; the answer key never appears in tool output.import_curriculumโ loads any markdown question file: read the raw file, extract each question + correct answer, emit them in the standard format. Used when the automatic parser can't make sense of a file's format. Loading a course does not start teaching โ the teacher waits for your go-ahead. Every load persists the course into the SQLite question store.quizโ legacy quick-test mode over the whole bank; the v0.3 UI prefers the LLM-free quiz popup instead.analyze_quizโ post-quiz LLM analysis: pass the run id from the popup ("Quiz finished (run N)"), get the run's questions (hidden answer keys + hints) and the user's answers, grade each (correct/partial/wrong/no-answer), record gaps, and walk the misses Socratically;done: truemarks the run analyzed.note_gapโ records a gap (wrong | vague | missing | exposed) with the user's verbatim words + the knowledge point you identified; persisted to the ledger and the session log.grade_answerโ grades against the hidden answer key; updates each open gap's FSRS schedule;correctmarks gaps mastered.retestโ returns due gaps; drill them one at a time, thengrade_answer.summaryโ pulls the ledger for the end-of-session knowledge-point report.
Per the policy section (injected only while teacher mode is active): hard Socratic mode โ never reveal the answer, one micro-question at a time; hints are generated by the teacher from the user's answers (escalating, never the answer); knowledge-lack fallback โ the same micro-question fails twice or the user says "I don't know what X is" โ explain the missing knowledge point concisely (definition + example), never repeat the question a third time; "just tell me" โ answer + record an exposed gap.
Input formats
The automatic parser is format-tolerant: it recognizes questions in many shapes (numbered items, Q1: items, ## Q<n>: headings), answer markers (โ Answer:, Answer:, ็ญๆก๏ผ, โ
/bold multiple-choice options, <!-- answer: --> comments), and hints (> Key words:, > Trap:, > ๅ
ณ้ฎ่ฏ๏ผ, comments). Questions that carry no answer/options/hints are treated as prose and skipped.
If a file still won't parse, tell the teacher "import this file" โ it converts the file with import_curriculum (LLM-assisted) into the standard format. The markdown file supplies questions and answers; hints and knowledge points always come from the teacher's own generation, not from the file.
Why it exists
Chatbots explain at you; cognitive science says that's the least effective way to teach. Retrieval practice, spaced reviews, and making the student produce the answer (pretesting) beat passive reading โ even when the first attempt is wrong. dsh-teacher builds that evidence into the DSH agent. See the landscape survey in [docs/PLAN.md ยง1](docs/PLAN.md).
Development
npm test # node:test โ zero runtime deps beyond DSH itselflib/โ pure logic (curriculum parser, FSRS-5, grading, folding, ledger, gap
projection, SQLite question store, quiz projection); fully unit-tested, no DSH imports.
index.jsโ the Cordis host plugin (prompt section, commands, tools, session
events, teacherGaps + teacherQuiz projections, the /dsh-teacher/quiz/submit route). Written in plain JS (no build step); imports @deepseek-ai/dsh-tools and zod at runtime, resolved from the DSH install / npm.
lib/client.jsโ the Web client: a hand-rolled__ModuleLoader__bundle
(plain JS + React.createElement, no build step) declaring dsh.client in package.json and registered at the ./client exports subpath.
- Ledger location:
$DSH_HOME/state/dsh-teacher/ledger.db(falls back to.json). - Question store:
$DSH_HOME/state/dsh-teacher/question-store.db(falls back to
.json) โ a single global pool of courses shared by every teacher session; the legacy v0.2 per-workspace JSON course files are imported once on first load.
License
MIT