improve signed reads, crypto hardening, and scraper transport

app/services/kol_analysis.py

@@ -315,6 +315,8 @@ async def extract_kol_signal(
     if post_type not in valid_post_types:
         post_type = "other"
 
+    tier = _derive_tier(cleaned, tvt_score)
+
     return {
         "summary": (data.get("summary") or "").strip() or None,
         "post_type": post_type,
@@ -322,6 +324,33 @@ async def extract_kol_signal(
         "talks_vs_trades_score": tvt_score,
         # Keep old boolean for any callers that still check it
         "talks_vs_trades_flag": tvt_score >= 0.5,
+        # tier mirrors x_analysis' vocabulary (trade_signal / directional /
+        # noise) so blog/substack/podcast posts get the same SIGNAL/VIEW UI
+        # badges + the "Signals only" filter that Twitter posts already have.
+        "tier": tier,
         "model": model,
         "version": ANALYSIS_VERSION,
     }
+
+
+def _derive_tier(tickers: list[dict], tvt_score: float) -> str:
+    """Map kol_analysis output → the trade_signal/directional/noise tiers that
+    x_analysis emits directly. Non-Twitter analyzers don't ask the model for a
+    tier, so we derive one from the per-ticker conviction + the talks-vs-trades
+    (divergence) score. Without this, blog/substack/podcast rows have tier=NULL
+    and the "Signals only" filter + SIGNAL/VIEW badges never apply to them.
+
+      * directional ticker = an explicit non-"mention" action (buy/sell/
+        reduce/bullish/bearish).
+      * trade_signal = high conviction (>= 0.6) on a directional ticker, or a
+        strong talks-vs-trades divergence (>= 0.6) — the platform's top signal.
+      * directional  = a directional view exists but below the trade_signal bar.
+      * noise        = no directional ticker and no notable divergence.
+    """
+    directional = [t for t in tickers if (t.get("action") or "mention") != "mention"]
+    max_conv = max((float(t.get("conviction") or 0) for t in directional), default=0.0)
+    if max_conv >= 0.6 or tvt_score >= 0.6:
+        return "trade_signal"
+    if directional or tvt_score >= 0.5:
+        return "directional"
+    return "noise"