fix: Fixed Incorrect expression

doc/AGENTS.md

@@ -68,7 +68,7 @@ We use a tiered model strategy to balance intelligence and latency:
 
 In `app.py`, we implement a unique **Exclusive MCP Connection**:
 
-```python
+```
 # Pseudo-code logic from app.py
 AGENT_TOOL_MAP = {
     "scout": "search_and_offload",

doc/ARCHITECTURE.md

@@ -47,7 +47,7 @@ Traditional agents pass massive JSON blobs (search results, reviews, coordinates
   1. Scout finds 50+ locations, saves them to poi_repo, and returns {"scout_ref": "uuid"} to the Leader.
   2. Leader passes this UUID to the Optimizer.
   3. Optimizer loads data from the repo, solves the TSPTW problem, and saves the result.
-  * Result: Reduces token consumption by ~90% for complex trips.
+  * Result: Reduces token consumption by ~75% for complex trips.
 
 2. Exclusive MCP Channels (Tool Isolation)
 In standard multi-agent setups, all tools are often dumped into a shared context, confusing the LLM (e.g., the "Optimizer" trying to use "Weather" tools).