Phase 5: iteration & polish (visualizations, goal history, smart tagging)

Final roadmap phase. No DB migration — it reads data already captured.

- Goal-evolution history: GET /discovery/profile/me/goal-history derives a
  per-goal timeline from the profile_revision snapshots (pure aggregator in
  app/services/profile_history.py).
- Smart tagging: POST /discovery/integration/suggest-foundation suggests which
  foundation a task builds toward + rationale/confidence (FoundationTagger,
  app/services/tagging.py). Suggestion only; the person confirms by posting the
  task mapping.
- Deeper goal-refinement: the reflect loop accepts an optional focus ("goals")
  that steers the coach toward sharpening goals — still mirror, not compass.
- Visualizations: visuals.html renders an Ikigai Venn and an Enneagram diagram
  (plain-language callouts, not the raw type number) plus the goal-evolution
  timeline; linked from profile.html.

Tests: 99 passing (added pure goal-history tests, goal-history + suggest
endpoint tests, reflect-focus passthrough; run in-container). README updated.

This completes the ImpactFlow Vision roadmap (Phases 1-5) on the Discovery side.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

app/schemas.py

@@ -77,6 +77,9 @@ class ConfirmResponse(BaseModel):
 class ReflectRequest(BaseModel):
     # Empty/omitted starts the loop (the coach's opening reflection).
     message: str = ""
+    # Phase 5: optional refinement focus, e.g. "goals" to steer the coach
+    # toward sharpening the near/long-term goals.
+    focus: str = ""
 
 
 class ReflectionMessageOut(BaseModel):
@@ -194,6 +197,31 @@ class WorkPatternsOut(BaseModel):
     neglected: list[str]
 
 
+# -- Phase 5: iteration & polish ---------------------------------------------
+
+
+class GoalHistoryEntry(BaseModel):
+    value: Optional[str] = None
+    source: Optional[str] = None
+    at: Optional[datetime] = None
+
+
+class GoalHistoryOut(BaseModel):
+    short_term_goals: list[GoalHistoryEntry]
+    long_term_goals: list[GoalHistoryEntry]
+
+
+class SuggestFoundationRequest(BaseModel):
+    task_label: str
+
+
+class SuggestFoundationOut(BaseModel):
+    foundation: str
+    label: str
+    rationale: str = ""
+    confidence: str = "low"
+
+
 class ConversationResponse(BaseModel):
     id: str
     user_id: str