fix: Correct tool count from 9/10 to 11 tools across all documentation

CRITICAL CONSISTENCY FIX:

Actual verified count from mcp_tools.py:
- 11 tools (

@gr
.mcp.tool() decorators)
- 3 resources (

@gr
.mcp.resource())
- 3 prompts (

@gr
.mcp.prompt())
- Total: 17 MCP components

Changes in app.py:
- Line 4: Updated docstring header: 10 tools → 11 tools
- Lines 30-41: Added missing 'analyze_results' tool to tools list
- Line 115: Updated UI text: 10 tools → 11 tools
- Line 143: Updated ecosystem description: 10 tools → 11 tools
- Lines 1443-1444: Updated MCP section: 10 tools → 11 tools, added analyze_results to tool list

Changes in README.md:
- Line 119: 15 Total Components (9 Tools) → 17 Total Components (11 Tools)
- Line 121: 'Nine Production-Ready Tools' → 'Eleven Production-Ready Tools'
- Lines 896-900: Changelog updated: 15 components → 17 components, added missing tools

Missing tools now documented:
- analyze_results (detailed test result analysis)
- generate_prompt_template (custom prompt generation)

This resolves major discrepancies where different sections claimed 9, 10, or 15 components.

README.md

@@ -116,9 +116,9 @@ All analysis is powered by **Google Gemini 2.5 Pro** for intelligent, context-aw
 - ✅ **Testing Interface**: Beautiful Gradio UI for testing all components
 - ✅ **Enterprise Focus**: Cost optimization, debugging, decision support, and custom dataset generation
 - ✅ **Google Gemini Powered**: Leverages Gemini 2.5 Pro for intelligent analysis
-- ✅ **15 Total Components**: 9 Tools + 3 Resources + 3 Prompts
+- ✅ **17 Total Components**: 11 Tools + 3 Resources + 3 Prompts
 
-### 🛠️ Nine Production-Ready Tools
+### 🛠️ Eleven Production-Ready Tools
 
 #### 1. analyze_leaderboard
 
@@ -893,11 +893,11 @@ For issues or questions:
 
 ### v1.0.0 (2025-11-14)
 - Initial release for MCP Hackathon
-- **Complete MCP Implementation**: 15 components total
-  - 9 AI-powered and optimized tools:
-    - analyze_leaderboard, debug_trace, estimate_cost, compare_runs (AI-powered)
+- **Complete MCP Implementation**: 17 components total
+  - 11 AI-powered and optimized tools:
+    - analyze_leaderboard, debug_trace, estimate_cost, compare_runs, analyze_results (AI-powered analysis)
     - get_top_performers, get_leaderboard_summary (optimized for token reduction)
-    - get_dataset, generate_synthetic_dataset, push_dataset_to_hub (data management)
+    - get_dataset, generate_synthetic_dataset, generate_prompt_template, push_dataset_to_hub (data management)
   - 3 data resources (leaderboard, trace, cost data)
   - 3 prompt templates (analysis, debug, optimization)
 - Gradio native MCP support with decorators (`@gr.mcp.*`)

app.py

@@ -2,7 +2,7 @@
 TraceMind MCP Server - Hugging Face Space Entry Point (Track 1)
 
 This file serves as the entry point for HuggingFace Space deployment.
-Exposes 10 AI-powered MCP tools + 3 Resources + 3 Prompts via Gradio's native MCP support.
+Exposes 11 AI-powered MCP tools + 3 Resources + 3 Prompts via Gradio's native MCP support.
 
 Built on Open Source Foundation:
     🔭 TraceVerde (genai_otel_instrument) - Automatic OpenTelemetry instrumentation
@@ -32,6 +32,7 @@ Tools Provided:
     🐛 debug_trace - Debug agent execution traces with AI
     💰 estimate_cost - Predict evaluation costs before running
     ⚖️ compare_runs - Compare evaluation runs with AI analysis
+    📋 analyze_results - Analyze detailed test results with optimization recommendations
     🏆 get_top_performers - Get top N models from leaderboard (optimized)
     📈 get_leaderboard_summary - Get leaderboard overview statistics
     📦 get_dataset - Load SMOLTRACE datasets as JSON
@@ -111,7 +112,7 @@ def create_gradio_ui():
         gr.Markdown("""
         **Track 1 Submission**: Building MCP (Enterprise)
 
-        *AI-powered MCP server providing 10 tools, 3 resources, and 3 prompts for agent evaluation analysis.*
+        *AI-powered MCP server providing 11 tools, 3 resources, and 3 prompts for agent evaluation analysis.*
         """)
 
         # TraceMind Ecosystem (Accordion)
@@ -139,7 +140,7 @@ def create_gradio_ui():
             **Track 1: Building MCP (Enterprise)**
             - Provides AI-powered MCP tools for analyzing evaluation data
             - Uses Google Gemini 2.5 Pro for intelligent insights
-            - 10 tools + 3 resources + 3 prompts
+            - 11 tools + 3 resources + 3 prompts
             - [HF Space](https://huggingface.co/spaces/MCP-1st-Birthday/TraceMind-mcp-server)
 
             #### 🧠 TraceMind-AI
@@ -1439,8 +1440,8 @@ def create_gradio_ui():
 
                 ### What's Exposed via MCP:
 
-                #### 10 MCP Tools (AI-Powered & Optimized)
-                The ten tools above (`analyze_leaderboard`, `debug_trace`, `estimate_cost`, `compare_runs`, `get_top_performers`, `get_leaderboard_summary`, `get_dataset`, `generate_synthetic_dataset`, `generate_prompt_template`, `push_dataset_to_hub`)
+                #### 11 MCP Tools (AI-Powered & Optimized)
+                The eleven tools above (`analyze_leaderboard`, `debug_trace`, `estimate_cost`, `compare_runs`, `analyze_results`, `get_top_performers`, `get_leaderboard_summary`, `get_dataset`, `generate_synthetic_dataset`, `generate_prompt_template`, `push_dataset_to_hub`)
                 are automatically exposed as MCP tools and can be called from any MCP client.
 
                 #### 3 MCP Resources (Data Access)