extraction cleanup: events ledger dies, markdown source view, auditor-as-linker (2026-09-27 rulings)

The graph becomes raw reasoning chains only. Quiz outcomes and
understanding observations are no longer formalized; assessment
moves to the future practice module.

Events ledger removed end-to-end: LedgerEvent/LedgerEventKind/
UnderstandingLevel/ExtractionAttribution/AuditResult.dropped and
snapshot nodeObservations deleted from contracts; quizEvent builder
and the events step of mergeFindings gone; appendEvent/readEvents
dropped from the port and store; LEDGER_FILES loses events.jsonl
with a one-time purge of a stale file next to the nodes ledger;
graph-deletion and the delete dialog lose event purge + quiz-answer
impact counts; GraphSessionProposition becomes a pure birth list.

Whole-session markdown source view: new core/session-markdown.ts is
the shared formatting engine (id-anchored speaker blocks, quiz/
recall/question blocks, tool one-liners) — the extractor's prompt
view and the future user-facing export render from one engine.
Coverage fingerprints deliberately stay on the old line format
(content-hash semantics; re-formatting never re-opens covered
history). The whole session goes to the extractor — no phase cut.

Auditor refocused as the identity linker: never sees the source;
explores the graph via new auditor-specific tools in
agent/tools/graph.ts (find — glob over name/statement/aliases;
list_sessions; list_propositions with full statement text; no
timestamps) instead of an injected full-graph dump; equivalence
bias — paraphrases merge, only genuinely distinct propositions stay
apart; no drop channel, the extractor is fully trusted; may draw
bridging edges (typed follows/supports) between existing nodes and
the batch, resolved by the merger with chat-scoped message-less
provenance. Agentic loop, maxTurns 16.

UI: the node detail card gains an edges section above the sessions
list (follows-from / supported-by / what-follows / what-it-supports,
rendered only when present, click-to-select neighbors); the
understanding-note chips are gone.

Prober list_propositions reworded to what a session covered —
names only, no levels. docs/architecture.md + README updated to
the as-built pipeline. Gates: typecheck, 1059/1059, lint, build.

README.md

@@ -154,7 +154,7 @@ data/                           chats/ · graph/ (six ledgers + positions/source
 
 **The async sub-agent protocol (ack-and-steer).** `research` / `demo` / `visual` are server-executed tools: the call resolves immediately mid-turn with a fire-and-forget ack and the teacher keeps teaching; a background runner works in parallel (the client polls `/api/activity` and `/api/jobs`). On completion the runner builds a **steer message** — a user-role `UIMessage` whose text part is the model-facing result and whose `data-subagent-artifact` part carries the full result for the client — and the **wake pipeline** delivers it: a per-chat serialized queue waits for the turn to end and no question to be pending, then fires a server-side teacher turn that weaves the result into the lesson. Delivery is exactly-once (deterministic steer ids, delivered-flag checks at every claim point); stalled jobs are recovered on read; aborted jobs deliver an abort steer. The client adopts the wake turn through the same `turnInFlight` machinery as returning mid-stream (busy shimmer, composer gate) and renders steers as artifacts — never a bubble. Sub-agents **verify, never one-shot**: the demo-builder headlessly executes its HTML in system Chrome before delivery; the visual-maker renders each SVG and looks at it (vision-capable model — the `vision` slot in settings).
 
-**The knowledge graph (two channels, one writer).** The write channel: the extraction pipeline — extractor (LLM, tree-blind: sees only the transcript view — propositions as true statements, `follows`/`supports` edges, retroactive quiz attribution, one-word understanding observations) → auditor (LLM: sees findings + the current graph; drops anything without verbatim evidence, stamps each survivor with an identity verdict — link to an existing node or create) → merger (`mergeFindings`, deterministic: applies the verdicts, link-appends phrasings/provenance, rebuilds quiz events from the transcript's tool parts, dedupes, checkpoints coverage) → layout settle. Triggered when a chat's **uncovered tokens** (message-view fingerprints, `coverage.jsonl`) cross `graph.extractionChunkTokens` (a settings knob, default 4096, floor 500 — read fresh per turn); failure checkpoints nothing, the next trigger re-runs. The same pipeline serves the **notes front door** (`POST /api/graph/import`: any `*.md`/`*.txt` becomes a source; re-imports are idempotent by path hash). The read channel: `GET /api/graph` derives the snapshot from the ledgers — a pure read; the home view is a hand-rolled Canvas 2D renderer (one rAF loop, dirty-flag idle, d3-zoom camera, zoom-gated labels, cluster hulls) over a d3-force layout, with server-persisted render settings and drag-committed positions. Clusters are **birth-session groupings**: a node joins the cluster of the session that birthed it (a chat, or an imported notes file as a file-kind session), derived at read — no embedding pass, no naming pass. The teacher reaches the graph on its own terms through the gated prober tools (`list_sessions` / `list_propositions`, the `agent.graphTools` setting) — there is no automatic context injection.
+**The knowledge graph (two channels, one writer).** The write channel: the extraction pipeline — extractor (LLM: sees only the session, rendered as readable markdown by the shared `core/session-markdown.ts` engine — propositions as true statements, `follows`/`supports` edges with verbatim evidence; fully trusted, graph-blind) → auditor (LLM, an agentic loop that never sees the source: explores the existing graph through `find` / `list_sessions` / `list_propositions` tools, stamps each proposition with an identity verdict — link to an existing node (equivalence bias: paraphrases merge) or create — and may draw bridging edges between existing nodes and the new batch) → merger (`mergeFindings`, deterministic: applies the verdicts, link-appends phrasings/provenance, resolves and dedupes edges, checkpoints coverage) → layout settle. No quiz outcomes or understanding assessments live in the graph (2026-09-27 cleanup); assessment becomes practice-module territory. Triggered when a chat's **uncovered tokens** (message-view fingerprints, `coverage.jsonl`) cross `graph.extractionChunkTokens` (a settings knob, default 4096, floor 500 — read fresh per turn); failure checkpoints nothing, the next trigger re-runs. The same pipeline serves the **notes front door** (`POST /api/graph/import`: any `*.md`/`*.txt` becomes a source; re-imports are idempotent by path hash). The read channel: `GET /api/graph` derives the snapshot from the ledgers — a pure read; the home view is a hand-rolled Canvas 2D renderer (one rAF loop, dirty-flag idle, d3-zoom camera, zoom-gated labels, cluster hulls) over a d3-force layout, with server-persisted render settings and drag-committed positions. Clusters are **birth-session groupings**: a node joins the cluster of the session that birthed it (a chat, or an imported notes file as a file-kind session), derived at read — no embedding pass, no naming pass. The teacher reaches the graph on its own terms through the gated prober tools (`list_sessions` / `list_propositions`, the `agent.graphTools` setting) — there is no automatic context injection.
 
 **Dictation.** Optional speech-to-text: the server mints short-lived Deepgram tokens; audio streams browser→Deepgram over WebSocket, never through the server.