diff --git a/README.md b/README.md
index e2db74d..3663525 100644
--- a/README.md
+++ b/README.md
@@ -6,10 +6,8 @@ AI-powered Kubernetes monitoring and diagnostics tool that automatically detects
 
 - 🤖 **AI-Powered Diagnostics**: Uses LLM with function calling to analyze Kubernetes issues
 - 🔍 **Smart Event Detection**: Monitors pods and nodes for problems (CrashLoopBackOff, NotReady, high restarts, etc.)
-- 🧠 **Correlation Engine**: Detects patterns like mass pod failures and diagnoses the root cause (node issues) instead of individual symptoms
-- 📱 **Telegram Notifications**: Optional real-time alerts with automatic "resolved" status updates
-- ⚡ **Concurrent Processing**: Configurable parallel AI diagnosis requests with semaphore-based rate limiting
-- 🎯 **Resource-Aware**: Tracks pod CPU/memory requests and limits for better diagnostics
+- 🧠 **Correlation Engine**: Detects patterns like mass pod failures and diagnoses the root cause (node issues)
+- 📱 **Telegram Notifications**: Optional real-time alerts
 
 ## How It Works
 
@@ -17,7 +15,6 @@ AI-powered Kubernetes monitoring and diagnostics tool that automatically detects
 2. **Correlates** issues (e.g., if 5+ pods fail on same node within 60s, diagnose the node)
 3. **Analyzes** using AI with access to k8s API tools (get pod details, logs, node status)
 4. **Notifies** via Telegram with structured diagnostic reports
-5. **Tracks** issue resolution and updates notifications automatically
 
 ## Installation
 
@@ -40,10 +37,10 @@ cp config.toml.example config.toml
 # API Configuration (OpenAI-compatible)
 api_base = "http://localhost:11434/v1"  # Ollama, vLLM, etc.
 api_key = "your-key"
-model = "qwen3-tools:latest"
+model = "qwen3-tools:latest" # any model supporting tools
 
 # Concurrency
-max_concurrent_diagnoses = 1
+max_concurrent_diagnoses = 1 # parallel OpenAI API requests
 
 # Telegram (optional)
 telegram_bot_token = "your-bot-token"
@@ -66,7 +63,7 @@ KUBECONFIG=/path/to/kubeconfig cargo run --release
 ## Requirements
 
 - Rust 1.70+
-- Kubernetes cluster access (via kubeconfig)
+- Kubernetes cluster access (via kubeconfig or kubernetes service account)
 - OpenAI-compatible LLM endpoint with function calling support
   - Tested with: Ollama (qwen3-tools, devstral-small-2)
   - Should work with: OpenAI, vLLM, etc.
@@ -89,4 +86,4 @@ KUBECONFIG=/path/to/kubeconfig cargo run --release
 
 ## License
 
-MIT
+WTFPL