Pivot to text-first column-stack workspace + merge-with-review across AI artifacts

Workspace
- Pivot from "set of open panes" to a Finder-style miller column stack:
  TopBar / LeftSidebar / [section → entity → entity ...] / pinned text editor.
  openPanesStore is now an ordered Column[] with pushFrom / closeFrom /
  setStack; only one top-level section is rooted at a time.
- New entity column panes: Term, Block, Association, Constraint,
  Requirement, Finding. Click-through navigation truncates deeper
  columns automatically.
- LeftSidebar surfaces a pending-count chip per section (single-glance
  navigation cue) and spins its analyze ↻ via SVG Spinner whenever the
  LLM is working — including server-initiated runs caught by the runs
  poll, not just user-triggered ones.

Analyze pipeline + persistence
- Unified `concepts` pass (taxonomy + glossary in one LLM call) replaces
  the two-pass setup. Server still accepts ?section=taxonomy|glossary
  and normalizes them for back-compat.
- model / requirements / detection (assumptions, risks, inconsistencies)
  + cross-layer validation rules (X1–X4: stale term link, unlinked
  formalism, undefined linked term, prose-only term).
- Persistence: NarrativeDocument, ModelSnapshot, ChangelogEntry,
  TaxonomyTerm, RequirementEntry, Finding, AnalysisRun. Re-runs MERGE
  instead of replace: gentle update on existing items, suggested on new,
  deprecated on missing — same idiom for every artifact kind. User pins
  preserve "kept" decisions across re-analyses.
- Migrations: pivot_text_first, add_requirement_linked_term,
  term_review_state, review_state_for_reqs_and_findings,
  add_term_definition_pinned.

Concept ↔ ontology integration
- linkedTermId on Block / Association / Constraint / Requirement.
  PromoteToolbar lets the user formalize a concept inline: + Block /
  + Association / + Constraint / + Requirement, all routed through
  applyOps so undo/redo and SSE work for free.
- decideElement op for in-canvas keep/discard on review-pending model
  elements.

User-authored definitions
- TermColumn definition is click-to-edit. Save (Cmd-Enter / blur),
  Cancel (Esc), Reset to AI suggestion when pinned.
- definitionPinned flag on TaxonomyTerm: future Analyze runs leave the
  user's text alone. setTermDefinition repo function + POST
  /api/projects/[id]/terms/[termId]/definition endpoint.
- mergeTaxonomySuggestion + applyGlossaryDefinitions both pin-aware.

UX/UI
- StatusChip: single component for all state idioms (suggested,
  deprecated, accepted, dismissed, resolved, severity, validation code,
  confidence, warn). Replaces 5+ ad-hoc badge classes.
- PaneControls (PaneViewTabs + PaneFilterChip): separates view-mode
  toggles from filter chips so toggling Pending no longer flips you off
  the current view.
- PaneEmpty: unified empty-state with title + hint + action.
- PaneDrawer: collapsible groups for Pending / Discarded review; cards
  group as Kept (top) → Pending (bottom drawer) → Discarded (Findings
  only, hidden when empty). Restore action recovers dismissed/resolved
  findings.
- ConceptCard unifies Tree and A–Z views in Concepts; only Tree parents
  carry the chevron (no empty placeholder offset).
- Type + spacing tokens (--text-xs..xl, --space-1..6, --lh-tight/ui/
  prose, --radius-*) replace every ad-hoc value.
- Buttons standardized to body sans 500 (was a mishmash of mono / display).
- Card shells unified across Concepts / Requirements / Findings.

Cleanup
- Removed: LeftRail, FindingsPanel, IssuesPanel, SocratesDock,
  ProposalCard, SlashMenu, SlashExtension, slashSuggestion,
  CanvasHeader, TaxonomyPane, GlossaryPane, TermDetail (popover; now
  TermColumn).
- Section ids in openPanesStore: dropped taxonomy/glossary, added
  concepts. localStorage migration runs on hydrate.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

apps/web/lib/llm/prompts/socrates/interview.md

@@ -0,0 +1,53 @@
+# Mode: Seed interview (live, per-turn)
+
+You are conducting an opening interview with a product manager who is starting a new idea inside Socrata. Goal: produce a `SeedDraft` (problem, target user, desired outcome, optional initial hypothesis, optional constraints) that's specific enough to generate a coherent SysML model from.
+
+You are stateful across turns — each call gives you the running thread + the draft you've extracted so far. Improve the draft, ask the next question, and signal when there's enough to proceed.
+
+## Behaviour
+
+- **Maximum 5 user turns total** before you mark the interview ready. Don't drag it out.
+- Each turn: ask exactly ONE question. Don't pile.
+- Question 1: the problem in one sentence — the smallest, most honest version.
+- Question 2: target user, with a specificity probe ("which users, why now").
+- Question 3: desired outcome — what changes when this exists.
+- Question 4: a tension probe — name a likely tension you see and ask which side they're on.
+- Question 5: explicit constraints — anything regulatory, ethical, technical that's non-negotiable.
+
+## Updating the draft
+
+- Each turn, update the draft fields based on what you've learned. Use the user's own register where possible.
+- Leave a field empty (`""`) until the user has actually addressed it. Don't fabricate.
+- `confidence` (0..1) is your honest read on whether the draft is specific enough to generate a useful model. Generic platitudes → low. Specific, falsifiable → high.
+
+## Ready signal
+
+Set `ready: true` when:
+- All five core fields (problem, targetUser, desiredOutcome) are populated AND specific, OR
+- 5 user turns have elapsed AND the draft has at least problem + targetUser + desiredOutcome.
+
+When `ready: true`, your `text` should be a brief synthesis ("Here's what I understand…") plus an explicit "Ready to generate the initial model — say go or refine.", not another question.
+
+## Voice
+
+Per character.md. Question-led, economical, no filler. Press for specificity if an answer is vague — "what specifically does X mean here?" beats "tell me more".
+
+## Output schema (strict)
+
+```json
+{
+  "text": "string (1–3 sentences)",
+  "draft": {
+    "title": "string (a working name for the project)",
+    "problem": "string",
+    "targetUser": "string",
+    "desiredOutcome": "string",
+    "initialHypothesis": "string (optional)",
+    "constraints": ["string"]
+  },
+  "confidence": 0.0,
+  "ready": false
+}
+```
+
+Return ONLY the JSON object. No prose preamble, no code fences.