Update external API examples (Claude, Gemini, etc.)

README.md

@@ -129,7 +129,7 @@ This model runs as a fast "router" before the main agent model:
    - **Score 0-25** → VL-2B (simple tasks: greetings, time, file listing)
    - **Score 26-50** → VL-4B (moderate: file editing, searches)
    - **Score 51-75** → VL-4B + thinking mode (complex: code generation, multi-step)
-   - **Score 76-100** → External API / GitHub Copilot (expert: debugging, architecture)
+   - **Score 76-100** → External API like Claude, Gemini, etc. (expert: multi-step code, debugging, architecture)
 4. Result: Right-sized model for every task, faster responses, lower cost
 
 **Why a Combined Model?**
@@ -193,7 +193,7 @@ User Request: "Write a Python script to process CSV files"
      ├─── Score 51-75 ───────────► AGiXT-Qwen3-VL-4B + thinking (complex)
      │    "Write a CSV processor" → 65  ◄── This request
      │
-     └─── Score 76-100 ──────────► External API / Copilot (expert)
+     └─── Score 76-100 ──────────► External API (Claude, Gemini, etc.)
           "Debug this race condition" → 85
 ```
 
@@ -205,7 +205,7 @@ User Request: "Write a Python script to process CSV files"
    - **0-25 (Simple)**: VL-2B handles greetings, time queries, basic file listings
    - **26-50 (Moderate)**: VL-4B for file editing, web searches, data retrieval
    - **51-75 (Complex)**: VL-4B with extended thinking for code generation, multi-step tasks
-   - **76-100 (Expert)**: Routes to external APIs (GitHub Copilot) for debugging, architecture, algorithms
+   - **76-100 (Expert)**: Routes to external APIs (Claude, Gemini, GPT-4, etc.) for multi-step code generation, debugging, architecture
 
 3. **Ability Context**: The selected ability helps the main model focus. If AbilitySelect returns `65|Write to File`, the main model knows this is a file-writing task requiring code generation.