Stock-picker plans never hold an index fund unless the profile is cautious or a loss tolerance is stated

README.md

@@ -214,6 +214,10 @@ Recommendation discipline for every book with a usable DCF range:
   model applies, P/E vs own history). One-year performance is a ±3 tie-breaker only; a breached
   loss tolerance costs 8; the weakest pillar caps the total (one broken pillar cannot be
   outvoted by strong prospects).
+- **A stock-picker's plan never holds an index fund** — for a book of 12+ single names with no
+  cautious profile or stated loss tolerance, no ETF enters the candidate pool at all: sector
+  gaps, ballast and diversification are expressed through single names. A conservative profile,
+  a short horizon or a loss tolerance brings defensive instruments back.
 - **Stock-picker books get stock ideas** — a book of 12+ single names is treated as a
   stock-picker's: the CIO sees single names first, at least two alternatives are single stocks
   and at most one is an instrument; smaller books or de-risking needs still get instruments.

src/orchestrator.py

@@ -413,6 +413,8 @@ def run_analysis(rows: list[dict], emit, context: dict | None = None, budget_s:
             pass
     cards += _risk_cards(risk, holdings, context)
     needs = M.diagnose_needs(pm, risk, holdings, context)   # what THIS book needs — drives everything below
+    if M._tol_from_context(context) is not None:
+        needs["_loss_tol"] = {"weight": 0.0, "label": None}   # marker: instruments allowed as ballast
     _bg = cf.ThreadPoolExecutor(max_workers=2)
     strat_fut = _bg.submit(P.strategist_review, {
         "holdings": [{"ticker": h["symbol"], "sector": h["data"].get("sector"),
@@ -1080,8 +1082,10 @@ def _instrument_candidates(needs: dict, holdings: list[dict], risk: dict) -> lis
     if needs.get("_cautious"):          # a retiree's gap-filler is a defensive sector, never a tech fund
         gaps = [g for g in gaps if g in ("Utilities", "Consumer Defensive", "Healthcare")]
     fund_syms_local = {h["symbol"] for h in holdings if str(h["data"].get("quote_type") or "").upper() in M.FUND_TYPES}
-    if _stock_picker(holdings, fund_syms_local) and not needs.get("_cautious"):
-        gaps = []                       # a stock-picker fills a sector gap with a stock, not a sector fund
+    if _stock_picker(holdings, fund_syms_local) and not needs.get("_cautious") and not needs.get("_loss_tol"):
+        return []                       # a stock-picker's plan never holds an index fund: gaps, ballast and
+                                        # diversification are all expressed through single names (user rule);
+                                        # only a cautious profile or a stated loss tolerance brings instruments back
     for i in inst:
         if i.get("asset_class") == "sector_etf" and i.get("sector") in gaps[:4] and i["ticker"] not in held:
             out.append({"ticker": i["ticker"], "sector": i["sector"], "instrument": True, "need_target": "sector_gaps",