diff --git a/.Jules/palette.md b/.Jules/palette.md
new file mode 100644
index 0000000..3929bc1
--- /dev/null
+++ b/.Jules/palette.md
@@ -0,0 +1,3 @@
+## 2024-03-07 - Accessible Statistical/Financial Input Tooltips
+**Learning:** This application involves highly technical inputs (e.g., basis points, daily volume percentiles, rolling quantiles) that are obscure to less experienced users. Providing concrete, relatable examples inside the native Streamlit `help` parameter makes the interface significantly more intuitive and usable.
+**Action:** Always include concrete numeric examples (e.g., "10 bps = 0.10%", "21 days = 1 month") when adding or modifying statistical or financial input parameters across the design system.
diff --git a/src/dashboard.py b/src/dashboard.py
index 4156c1d..0139d93 100644
--- a/src/dashboard.py
+++ b/src/dashboard.py
@@ -168,16 +168,37 @@ def get_cache_key(*args) -> str:
             help="Lookback months for Momentum signal."
         )
     else:
-        factor_window = st.slider("Factor Beta Window (days)", 20, 252, 63, 7)
-        vol_window = st.slider("Regime Vol Window (days)", 10, 60, 21, 5)
-        adv_pct = st.slider("ADV Participation %", 0.01, 0.30, float(DEFAULT_ADV_PCT), 0.01)
+        factor_window = st.slider(
+            "Factor Beta Window (days)",
+            20,
+            252,
+            63,
+            7,
+            help="Rolling window for calculating beta to risk factors (e.g., 63 days = 3 months).",
+        )
+        vol_window = st.slider(
+            "Regime Vol Window (days)",
+            10,
+            60,
+            21,
+            5,
+            help="Rolling window for calculating realized volatility (e.g., 21 days = 1 month).",
+        )
+        adv_pct = st.slider(
+            "ADV Participation %",
+            0.01,
+            0.30,
+            float(DEFAULT_ADV_PCT),
+            0.01,
+            help="Target percentage of Average Daily Volume for trading (e.g., 0.10 = 10% of daily volume).",
+        )
 
     st.markdown("---")
     st.subheader("4. Research Rigor")
     use_oos = st.toggle(
         "Out-of-Sample Mode",
         value=False,
-        help="Uses expanding-window quantiles for regime classification to avoid look-ahead bias. Enable for rigorous backtesting."
+        help="Uses expanding-window quantiles for regime classification to avoid look-ahead bias. Enable for rigorous backtesting.",
     )
     if use_oos:
         st.success("✓ Look-ahead bias removed")
@@ -185,12 +206,25 @@ def get_cache_key(*args) -> str:
         st.info("Using full-sample quantiles (exploratory mode)")
 
     vol_q_high = st.slider(
-        "High Volatility Quantile", 0.5, 0.95, DEFAULT_VOL_QUANTILE_HIGH, 0.05
+        "High Volatility Quantile",
+        0.5,
+        0.95,
+        DEFAULT_VOL_QUANTILE_HIGH,
+        0.05,
+        help="Threshold for defining 'High' volatility regime (e.g., 0.75 = top 25% of historical volatility).",
     )
 
     if mode == "Single-Asset":
         st.subheader("5. Backtest Settings")
-        bt_cost = st.number_input("Transaction Cost (bps)", value=DEFAULT_COST_BPS, step=1) / 10000
+        bt_cost = (
+            st.number_input(
+                "Transaction Cost (bps)",
+                value=DEFAULT_COST_BPS,
+                step=1,
+                help="Cost per trade in basis points (e.g., 10 bps = 0.10%).",
+            )
+            / 10000
+        )
         allow_short = st.checkbox("Allow Short Selling?", value=False)
     else:
         st.subheader("5. Alert Thresholds")