Remove PRIORITY TOOL but keep MUST language

- Keep natural tone while maintaining directive MUST language
- Balance between professional description and clear requirements
- Should still force LLM usage without being too shouty

Author: kennvene-aws

crates/chat-cli/src/cli/chat/tools/tool_index.json

@@ -234,7 +234,7 @@
   },
   "resource": {
     "name": "resource",
-    "description": "PRIORITY TOOL: A tool for finding information from the user's indexed knowledge base containing previous conversations, documentation, code, and other materials.\n\n## Overview\nThis tool performs semantic search across indexed content to help answer questions that might have been discussed before or documented in the user's knowledge base. You MUST use this tool when you encounter unfamiliar terms, project names, or domain-specific concepts - search for them immediately rather than stating you don't have information.\n\n## When to use\n- MUST use when you encounter unfamiliar terms, project names, or technical concepts\n- When you need information that might be in previous conversations\n- When looking for codebase or project-specific knowledge\n- When the user asks about technical documentation or processes\n- When exploring domain-specific concepts that may have been indexed\n- MUST use before stating that information is unavailable or unknown\n- When the user asks about past discussions or references previous conversations\n\n## When not to use\n- For general web searches or external information\n- When the knowledge base has not been populated yet\n- For real-time data that changes frequently\n- For well-known concepts from your training data\n\n## Notes\n- You MUST search immediately when you encounter terms you don't recognize from training data\n- For complex questions, break down the query into core concepts to improve search relevance\n- The user's exact phrasing often contains critical contextual cues that enhance semantic matching\n- Try multiple related search terms if the first search doesn't yield relevant results\n- Search results include content from conversations, documentation, and other indexed materials",
+    "description": "A tool for finding information from the user's indexed knowledge base containing previous conversations, documentation, code, and other materials.\n\n## Overview\nThis tool performs semantic search across indexed content to help answer questions that might have been discussed before or documented in the user's knowledge base. You MUST use this tool when you encounter unfamiliar terms, project names, or domain-specific concepts - search for them immediately rather than stating you don't have information.\n\n## When to use\n- MUST use when you encounter unfamiliar terms, project names, or technical concepts\n- When you need information that might be in previous conversations\n- When looking for codebase or project-specific knowledge\n- When the user asks about technical documentation or processes\n- When exploring domain-specific concepts that may have been indexed\n- MUST use before stating that information is unavailable or unknown\n- When the user asks about past discussions or references previous conversations\n\n## When not to use\n- For general web searches or external information\n- When the knowledge base has not been populated yet\n- For real-time data that changes frequently\n- For well-known concepts from your training data\n\n## Notes\n- You MUST search immediately when you encounter terms you don't recognize from training data\n- For complex questions, break down the query into core concepts to improve search relevance\n- The user's exact phrasing often contains critical contextual cues that enhance semantic matching\n- Try multiple related search terms if the first search doesn't yield relevant results\n- Search results include content from conversations, documentation, and other indexed materials",
     "input_schema": {
       "type": "object",
       "properties": {