Add gem quality & model intelligence section

- Documented how gem quality improves with model size
- Added comparison table (7B vs 30B vs 70B+)
- Provided example gem JSON
- Added recommendation for production models

README.md

@@ -76,6 +76,28 @@ After:  Watching current session (93dc32bf... from Feb 25) ✅
 | **Gem Merging/Updating** | When user changes preference, old gem still exists. Need mechanism to update/contradict old gems. | Low |
 | **Importance Calibration** | All curator gems marked "medium" importance. Should dynamically assign based on significance. | Low |
 
+### Gem Quality & Model Intelligence
+
+**Gem quality improves significantly with smarter models:**
+
+| Model | Gem Quality | Example |
+|-------|-------------|---------|
+| **Small models (7B)** | Basic extraction, may miss nuance | "User likes local AI" |
+| **Medium models (30B)** | Better categorization, captures intent | "I prefer local AI over cloud services for privacy reasons" |
+| **Large models (70B+)** | Rich context, infers significance, better first-person conversion | "I decided to self-host AI tools because I value data privacy and want to avoid vendor lock-in" |
+
+**Example Gem (High Quality):**
+```json
+{
+  "text": "I decided to keep the installation simple and not include gems for the basic version",
+  "category": "decision",
+  "importance": "high"
+}
+```
+
+**Current:** Using `qwen3:30b-a3b-instruct` for extraction (good balance of quality/speed).  
+**Recommendation:** For production use, consider `qwen3:72b` or `deepseek-r1` for higher gem quality.
+
 ---
 
 ## Overview