- Chat now remounts per session (key={chat.id}): fresh StickToBottom,
fresh DockOverlay (no cross-session morph from the previous shell
height), fresh useChat.
- Conversation initial="instant" (was "smooth"): the mount scroll to
bottom is a jump, not a slide.
- DockOverlay skips the pending-question scroll/expand effect for the
session's INITIAL pending question (dock starts expanded; the initial
scroll positions us) — previously it fired a second smooth
scrollToBottom right after the library's initial scroll (the visible
'pause, then the quiz pops and pushes everything up').
- The dock-variant fade/rise no longer plays for the session's opening
variant; reserved for mid-session transitions.
Verified live: client-side switch settles at d=1px from the bottom within
one frame of content swap, dock open from the first frame, both
directions (quiz session, plain session).
The teaching agent no longer runs on pi. Stack:
- ToolLoopAgent (ai@7) + OpenRouter (OPENROUTER_API_KEY), model via LH_MODEL,
default anthropic/claude-sonnet-4.5 with reasoning tokens
- quiz/ask_user_question = client-side tools (no server execute): the call
lands as a typed tool part in input-available state; the card grades via
src/core/question-core.ts; addToolOutput sends the verdict; the teacher's
reaction continues the same assistant message
- resume-mid-quiz is free: the pending tool part persists in the transcript
- persistence: one JSON per chat (data/chats/), full UIMessage transcripts,
saved onFinish (also on abort)
- UI: AI Elements (owned copy-paste components, pruned to the five in use)
+ button-based QuizCard/AnsweredCard (ask answers never graded)
- pi fully removed: TUI, extensions, Fastify+WS server, bridge, custom
protocol all deleted (recoverable from git history)
- tests: question-core units carry over; chat-flow integration drives
handleChatRequest with MockLanguageModelV4 (48 tests, zero tokens);
render smoke tests guard the cards (renderToStaticMarkup)
Carried over unchanged: teacher system prompt, question-core, schema/
ledger/derive/extract pipeline, data model.
Amos