diff --git a/README.md b/README.md
index ad60aaa..edfccd5 100644
--- a/README.md
+++ b/README.md
@@ -92,6 +92,14 @@ Use a swarm of AI agents to generate a marketing plan for your business.
 ai marketing-plan
 ```
 
+### 8. Posture Coach (`ai posture`)
+
+Use the webcam and a tiny vision model to analyze your posture and focus.
+
+```bash
+ai posture
+```
+
 ## Tool Use Tools (`tooluse` command)
 
 ### 1. Podcast RSS Reader (`tooluse`)
diff --git a/poetry.lock b/poetry.lock
index 0183606..3117622 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -563,13 +563,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.6"
+version = "1.0.7"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpcore-1.0.6-py3-none-any.whl", hash = "sha256:27b59625743b85577a8c0e10e55b50b5368a4f2cfe8cc7bcfa9cf00829c2682f"},
-    {file = "httpcore-1.0.6.tar.gz", hash = "sha256:73f6dbd6eb8c21bbf7ef8efad555481853f5f6acdeaff1edb0694289269ee17f"},
+    {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"},
+    {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
 ]
 
 [package.dependencies]
@@ -699,6 +699,88 @@ files = [
 [package.dependencies]
 ansicon = {version = "*", markers = "platform_system == \"Windows\""}
 
+[[package]]
+name = "jiter"
+version = "0.7.1"
+description = "Fast iterable JSON parser."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "jiter-0.7.1-cp39-none-win32.whl", hash = "sha256:5c08adf93e41ce2755970e8aa95262298afe2bf58897fb9653c47cd93c3c6cdc"},
+    {file = "jiter-0.7.1-cp39-none-win_amd64.whl", hash = "sha256:6592f4067c74176e5f369228fb2995ed01400c9e8e1225fb73417183a5e635f0"},
+    {file = "jiter-0.7.1.tar.gz", hash = "sha256:448cf4f74f7363c34cdef26214da527e8eeffd88ba06d0b80b485ad0667baf5d"},
+]
+
 [[package]]
 name = "markdown-it-py"
 version = "3.0.0"
@@ -764,6 +846,30 @@ files = [
 [package.dependencies]
 httpx = ">=0.27.0,<0.28.0"
 
+[[package]]
+name = "openai"
+version = "1.54.4"
+description = "The official Python library for the openai API"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "openai-1.54.4-py3-none-any.whl", hash = "sha256:0d95cef99346bf9b6d7fbf57faf61a673924c3e34fa8af84c9ffe04660673a7e"},
+    {file = "openai-1.54.4.tar.gz", hash = "sha256:50f3656e45401c54e973fa05dc29f3f0b0d19348d685b2f7ddb4d92bf7b1b6bf"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tqdm = ">4"
+typing-extensions = ">=4.11,<5"
+
+[package.extras]
+datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
+
 [[package]]
 name = "packaging"
 version = "24.2"
@@ -1656,4 +1762,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "81910a386f81af2f51761d35d03774ff0f2cd4d1374cc5a5a0cd3e9e3fd48b42"
+content-hash = "ca37820d18082bb80476989cde3ed8f0d29fbc63e65b7af0b159b25c92cfe730"
diff --git a/pyproject.toml b/pyproject.toml
index db1b6ec..9d9b578 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "tool-use-ai"
-version = "1.1.6"
+version = "1.1.10"
 description = "Tools to simplify life with AI"
 authors = ["Ty Fiero <tyfierodev@gmail.com>", "Mike Bird <tooluseai@gmail.com>"]
 readme = "README.md"
diff --git a/src/tool_use/cli.py b/src/tool_use/cli.py
index 4648ecf..aea8946 100644
--- a/src/tool_use/cli.py
+++ b/src/tool_use/cli.py
@@ -1,9 +1,8 @@
 import sys
 import argparse
 import subprocess
-import pkg_resources
+from importlib.metadata import version, PackageNotFoundError
 from .scripts._script_dependencies import SCRIPT_DEPENDENCIES
-from .scripts import ai_cli, cal, obsidian_plugin, convert, transcribe, prioritize, activity_tracker, marketing_agency
 from .utils.config_wizard import setup_wizard, SCRIPT_INFO
 
 
@@ -13,8 +12,8 @@ def ensure_dependencies(script_name):
 
     for package in SCRIPT_DEPENDENCIES[script_name]:
         try:
-            pkg_resources.require(package)
-        except (pkg_resources.DistributionNotFound, pkg_resources.VersionConflict):
+            version(package)
+        except PackageNotFoundError:
             print(f"Installing required dependency: {package}")
             subprocess.check_call(
                 [sys.executable, "-m", "pip", "install", "--upgrade", package]
@@ -44,6 +43,7 @@ def main():
         "prioritize": "Brain dump and prioritize tasks",
         "log": "Track your activities",
         "marketing-plan": "Use a marketing agency of AI agents to create a marketing plan",
+        "posture": "Use the webcam and a tiny vision model to analyze your posture and focus",
     }
 
     for name, help_text in all_scripts.items():
@@ -68,22 +68,25 @@ def main():
 
         # Try to import dependencies, install if missing
         ensure_dependencies(script_name)
-
-        # Map script names to their modules
+        
+        # Map script names to their module paths
         script_modules = {
-            "do": ai_cli,
-            "make-obsidian-plugin": obsidian_plugin,
-            "cal": cal,
-            "convert": convert,
-            "transcribe": transcribe,
-            "prioritize": prioritize,
-            "log": activity_tracker,
-            "marketing-plan": marketing_agency,
+            "do": "ai_cli",
+            "make-obsidian-plugin": "obsidian_plugin",
+            "cal": "cal",
+            "convert": "convert",
+            "transcribe": "transcribe",
+            "prioritize": "prioritize",
+            "log": "activity_tracker",
+            "marketing-plan": "marketing_agency",
+            "posture": "posture",
         }
 
-        # Run the appropriate script
+        # Dynamic import of only the needed module
         if script_name in script_modules:
-            script_modules[script_name].main(script_args)
+            module_name = script_modules[script_name]
+            module = __import__(f"tool_use.scripts.{module_name}", fromlist=["main"])
+            module.main(script_args)
         else:
             print(f"Unknown script: {script_name}")
             sys.exit(1)
diff --git a/src/tool_use/scripts/_script_dependencies.py b/src/tool_use/scripts/_script_dependencies.py
index ebfeb98..de83627 100644
--- a/src/tool_use/scripts/_script_dependencies.py
+++ b/src/tool_use/scripts/_script_dependencies.py
@@ -31,4 +31,17 @@
     ],
     "log": [],
     "marketing-plan": ["rich", "openai", "swarm"],
+    "posture": [
+        "moondream",
+        "rich",
+        "opencv-python",
+        "pillow",
+        "pydantic",
+        "llama-index",
+        "numpy>=1.22.4,<1.29.0",
+        "scipy>=1.10.0",
+        "transformers",
+        "llama-index",
+        "llama-index-llms-ollama",
+    ],
 }
diff --git a/src/tool_use/scripts/posture.py b/src/tool_use/scripts/posture.py
new file mode 100644
index 0000000..7a79b47
--- /dev/null
+++ b/src/tool_use/scripts/posture.py
@@ -0,0 +1,442 @@
+import os
+import time
+import sys
+import json
+import cv2
+import numpy as np
+import subprocess
+from rich.console import Console
+from rich.panel import Panel
+from rich.layout import Layout
+from rich.live import Live
+from rich.table import Table
+from rich.text import Text
+from datetime import datetime
+from collections import deque
+import statistics
+from PIL import Image
+from pydantic import BaseModel
+from enum import Enum
+from typing import List
+from llama_index.core.bridge.pydantic import BaseModel
+from llama_index.core.tools import FunctionTool
+from llama_index.llms.ollama import Ollama
+from llama_index.core.llms import ChatMessage
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from ..config_manager import config_manager
+
+console = Console()
+
+
+
+class Moondream:
+    MODEL_ID = "vikhyatk/moondream2"
+    REVISION = "2024-08-26"
+    
+    def __init__(self):
+        print("Loading Moondream2 model...")
+        self.model = AutoModelForCausalLM.from_pretrained(
+            self.MODEL_ID,
+            trust_remote_code=True,
+            revision=self.REVISION
+        )
+        self.tokenizer = AutoTokenizer.from_pretrained(
+            self.MODEL_ID,
+            revision=self.REVISION
+        )
+        print("Moondream2 model loaded successfully!")
+            
+    def analyze_posture(self, image):
+            start_total = time.time()
+            
+            # Time image encoding
+            start_encode = time.time()
+            encoded_image = self.model.encode_image(image)
+            encode_time = time.time() - start_encode
+            print(f"Image encoding took {encode_time:.2f} seconds")
+            
+            # Check for focus
+            start_focus = time.time()
+            focus_answer = self.model.answer_question(
+                encoded_image,
+                "Look at this webcam image. Please provide several sentences that describe if there is a person there, and if so, if they are focused/distracted, or if they are slouching.",
+                self.tokenizer
+            )
+            focus_time = time.time() - start_focus
+            print(f"Focus analysis took {focus_time:.2f} seconds")
+            
+            # # Check for slouching
+            # start_posture = time.time()
+            # posture_answer = self.model.answer_question(
+            #     encoded_image,
+            #     "Is the person slouching or showing poor posture? Answer with just Yes or No.",
+            #     self.tokenizer
+            # )
+            
+            total_time = time.time() - start_total
+            print(f"\nTotal analysis time: {total_time:.2f} seconds")
+            print(f"Results: Focus: {focus_answer}\n")
+
+            return focus_answer.lower().strip() 
+
+class AnalysisResults(BaseModel):
+    """Results of analyzing the description of a webcam image"""
+    present: bool
+    focused: bool
+    slouching: bool
+    distracted: bool
+
+llm = Ollama(model="llama3.1:latest", request_timeout=120.0)
+sllm = llm.as_structured_llm(AnalysisResults)
+
+def extractDataFromMoondream(text: str) -> str:
+    prompt = f""" 
+    Determine the following information from the provided text:
+        1. Human is present
+        2. Human is focused on work
+        3. Human is not slouching
+        4. Human is not distracted
+        
+        {text}
+    """
+    try:
+        response = sllm.chat([ChatMessage(role="user", content=prompt)])
+        
+        # Create a dictionary with the analysis results
+        analysis = {
+            "present": False,
+            "focused": False,
+            "slouching": False,
+            "distracted": False
+        }
+        
+        # Parse the response content
+        if hasattr(response.message, 'content'):
+            content = response.message.content
+            if isinstance(content, str):
+                try:
+                    # Try to parse it as JSON first
+                    analysis = json.loads(content)
+                except json.JSONDecodeError:
+                    # If it's not JSON, try to parse the text response
+                    analysis["present"] = "present: true" in content.lower()
+                    analysis["focused"] = "focused: true" in content.lower()
+                    analysis["slouching"] = "slouching: true" in content.lower()
+                    analysis["distracted"] = "distracted: true" in content.lower()
+            elif isinstance(content, dict):
+                analysis = content
+        
+        # Convert the analysis to a JSON string
+        return json.dumps(analysis)
+        
+    except Exception as e:
+        print(f"Error in extractDataFromMoondream: {e}")
+        # Return a default response if there's an error
+        return json.dumps({
+            "present": False,
+            "focused": False,
+            "slouching": False,
+            "distracted": False
+        })
+        
+        
+class WebcamHandler:
+    def __init__(
+        self, 
+        capture_interval=10, 
+        save_images=False, 
+        save_directory="captured_images",
+        resize_factor=0.5,
+        jpeg_quality=85
+    ):
+        self.capture_interval = capture_interval
+        self.save_images = save_images
+        self.save_directory = save_directory
+        self.resize_factor = resize_factor
+        self.jpeg_quality = jpeg_quality
+        
+        if save_images:
+            os.makedirs(save_directory, exist_ok=True)
+        
+        self.camera = None
+        self.initialize_camera()
+
+    def initialize_camera(self):
+        """Initialize the webcam with proper error handling"""
+        # Try to open the camera
+        self.camera = cv2.VideoCapture(0)
+        
+        if not self.camera.isOpened():
+            if sys.platform == "darwin":  # macOS
+                print("Camera access denied. Attempting to fix...")
+                print("Please grant camera permissions in System Preferences -> Security & Privacy -> Camera")
+                print("You might need to run: 'tccutil reset Camera' in Terminal with admin privileges")
+                
+                try:
+                    subprocess.run(['tccutil', 'reset', 'Camera'], check=True)
+                    print("Camera permissions reset. Please run the program again.")
+                except subprocess.CalledProcessError:
+                    print("Failed to reset camera permissions automatically.")
+                except FileNotFoundError:
+                    print("Could not find tccutil. Please reset permissions manually.")
+                
+            else:  # Other platforms
+                print("Could not open webcam. Please check if:")
+                print("1. Your webcam is connected")
+                print("2. It's not being used by another application")
+                print("3. You have granted necessary permissions")
+            
+            raise RuntimeError("Could not open webcam. Please check permissions and try again.")
+
+        # Test capture to ensure camera is working
+        ret, _ = self.camera.read()
+        if not ret:
+            self.camera.release()
+            raise RuntimeError("Camera opened but failed to capture. Please check if it's being used by another application.")
+
+    def capture_frame(self):
+        """Capture a frame from webcam and return as PIL Image"""
+        if self.camera is None or not self.camera.isOpened():
+            self.initialize_camera()
+
+        ret, frame = self.camera.read()
+        if not ret:
+            print("Failed to capture frame. Attempting to reinitialize camera...")
+            if self.camera is not None:
+                self.camera.release()
+            self.initialize_camera()
+            ret, frame = self.camera.read()
+            if not ret:
+                raise RuntimeError("Failed to capture frame even after reinitializing camera")
+
+        # Convert BGR to RGB
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        
+        # Convert to PIL Image
+        image = Image.fromarray(rgb_frame)
+        
+        # Resize based on resize_factor
+        width, height = image.size
+        new_width = int(width * self.resize_factor)
+        new_height = int(height * self.resize_factor)
+        image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
+
+        if self.save_images:
+            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+            save_path = os.path.join(self.save_directory, f"frame_{timestamp}.jpg")
+            image.save(save_path, "JPEG", quality=self.jpeg_quality)
+            return image, save_path
+        
+        return image, None
+
+    def process_saved_image(self, image_path: str):
+        """Process a saved image (e.g., move it to an archive folder or delete it)"""
+        if os.path.exists(image_path):
+            # For now, we'll just delete the temporary image
+            # You could modify this to move it to an archive folder instead
+            os.remove(image_path)
+
+    def __del__(self):
+        if self.camera is not None:
+            self.camera.release()
+        
+
+class ProductivityCoach:
+    def __init__(
+        self, 
+        capture_interval=10,
+        save_images=False,
+        resize_factor=0.5,
+        jpeg_quality=85,
+    ):
+        # Initialize with a fancy loading display
+        with console.status("[bold green]Initializing Productivity Coach...", spinner="dots"):
+            self.moondream = Moondream()
+            self.webcam = WebcamHandler(
+                capture_interval=capture_interval,
+                save_images=save_images,
+                resize_factor=resize_factor,
+                jpeg_quality=jpeg_quality
+            )
+            self.capture_interval = capture_interval
+            
+            # Stats tracking
+            self.stats = {
+                "total_frames": 0,
+                "focused_frames": 0,
+                "slouching_frames": 0,
+                "distracted_frames": 0,
+                "start_time": datetime.now(),
+                "focus_history": deque(maxlen=50),  # Keep last 50 readings
+            }
+
+    def generate_layout(self) -> Layout:
+        layout = Layout()
+        
+        layout.split(
+            Layout(name="header", size=3),
+            Layout(name="main"),
+            Layout(name="footer", size=3)
+        )
+        
+        layout["main"].split_row(
+            Layout(name="stats"),
+            Layout(name="current_status"),
+        )
+        
+        return layout
+
+    def make_stats_panel(self) -> Panel:
+        duration = datetime.now() - self.stats["start_time"]
+        hours = duration.seconds // 3600
+        minutes = (duration.seconds % 3600) // 60
+        
+        # Calculate percentages
+        total = max(1, self.stats["total_frames"])
+        focus_rate = (self.stats["focused_frames"] / total) * 100
+        slouch_rate = (self.stats["slouching_frames"] / total) * 100
+        distraction_rate = (self.stats["distracted_frames"] / total) * 100
+        
+        # Calculate recent focus trend
+        recent_focus = list(self.stats["focus_history"])
+        trend = "→"
+        if len(recent_focus) > 5:
+            recent_avg = statistics.mean(recent_focus[-5:])
+            older_avg = statistics.mean(recent_focus[-10:-5])
+            if recent_avg > older_avg + 0.1:
+                trend = "↑"
+            elif recent_avg < older_avg - 0.1:
+                trend = "↓"
+
+        stats_table = Table(show_header=False, box=None)
+        stats_table.add_row("Session Duration:", f"{hours:02d}:{minutes:02d}")
+        stats_table.add_row("Total Frames:", str(self.stats["total_frames"]))
+        stats_table.add_row("Focus Rate:", f"{focus_rate:.1f}% {trend}")
+        stats_table.add_row("Slouching Rate:", f"{slouch_rate:.1f}%")
+        stats_table.add_row("Distraction Rate:", f"{distraction_rate:.1f}%")
+        
+        return Panel(stats_table, title="[bold]Session Statistics", border_style="blue")
+
+    def make_status_panel(self, status_data) -> Panel:
+        status_text = Text()
+        
+        # Focus Status
+        if status_data["focused"]:
+            status_text.append("🎯 Focused\n", style="bold green")
+        else:
+            status_text.append("😶‍🌫️ Distracted\n", style="bold red")
+            
+        # Posture Status
+        if status_data["slouching"]:
+            status_text.append("🪑 Poor Posture\n", style="bold red")
+        else:
+            status_text.append("👍 Good Posture\n", style="bold green")
+            
+        # Presence Status
+        if status_data["present"]:
+            status_text.append("👤 Present\n", style="bold green")
+        else:
+            status_text.append("❓ Not Detected\n", style="bold yellow")
+            
+        return Panel(status_text, title="[bold]Current Status", border_style="green")
+
+    def update_stats(self, status_str: str):
+        # Parse the JSON string into a dictionary
+        try:
+            status = json.loads(status_str)
+        except json.JSONDecodeError:
+            console.print("[bold red]Error parsing status data[/]")
+            return
+
+        self.stats["total_frames"] += 1
+        if status.get("focused", False):
+            self.stats["focused_frames"] += 1
+        if status.get("slouching", False):
+            self.stats["slouching_frames"] += 1
+        if status.get("distracted", False):
+            self.stats["distracted_frames"] += 1
+            
+        # Update focus history (1 for focused, 0 for not)
+        self.stats["focus_history"].append(1 if status.get("focused", False) else 0)
+
+    def run(self):
+        layout = self.generate_layout()
+        
+        # Header and footer
+        layout["header"].update(Panel(
+            "[bold blue]Productivity Coach[/] - Press Ctrl+C to exit",
+            style="bold white on blue"
+        ))
+        layout["footer"].update(Panel(
+            f"Capturing every {self.capture_interval}s • Image Size: {self.webcam.resize_factor*100:.0f}% • JPEG Quality: {self.webcam.jpeg_quality}",
+            style="bold white on blue"
+        ))
+        
+        # Initialize the panels with default content
+        layout["stats"].update(self.make_stats_panel())
+        layout["current_status"].update(self.make_status_panel({
+            "present": False,
+            "focused": False,
+            "slouching": False,
+            "distracted": False
+        }))
+        
+        with Live(layout, refresh_per_second=1, screen=True):
+            try:
+                while True:
+                    # Capture and analyze frame
+                    image, temp_path = self.webcam.capture_frame()
+                    results = self.moondream.analyze_posture(image)
+                    status_str = extractDataFromMoondream(results)
+                    
+                    try:
+                        status_data = json.loads(status_str)
+                        # Update stats
+                        self.update_stats(status_str)
+                        
+                        # Update panels
+                        layout["stats"].update(self.make_stats_panel())
+                        layout["current_status"].update(self.make_status_panel(status_data))
+                    except json.JSONDecodeError:
+                        console.print("[bold red]Error parsing status data[/]")
+                    
+                    # Process saved image
+                    if temp_path:
+                        self.webcam.process_saved_image(temp_path)
+                    
+                    time.sleep(self.capture_interval)
+                    
+            except KeyboardInterrupt:
+                console.print("\n[bold red]Stopping Productivity Coach...[/]")
+
+def main(args=None):
+    tool_config = config_manager.get_tool_config("posture")
+    max_retries = 3
+    retry_delay = 5
+    capture_interval = tool_config.get("capture_interval", 10)
+    save_images = tool_config.get("save_images", False)
+    
+    for attempt in range(max_retries):
+        try:
+            print(f"Attempt {attempt + 1} of {max_retries} to start Productivity Coach...")
+            coach = ProductivityCoach(capture_interval=capture_interval, save_images=save_images)
+            coach.run()
+            break
+        except RuntimeError as e:
+            print(f"\nError: {e}")
+            if attempt < max_retries - 1:
+                print(f"Retrying in {retry_delay} seconds...")
+                time.sleep(retry_delay)
+            else:
+                print("\nFailed to initialize after multiple attempts.")
+                print("Please ensure your webcam is connected and permissions are granted.")
+                if sys.platform == "darwin":
+                    print("\nOn macOS, try these steps:")
+                    print("1. Open System Preferences")
+                    print("2. Go to Security & Privacy -> Privacy -> Camera")
+                    print("3. Ensure your terminal/IDE has camera permissions")
+                    print("4. Run 'tccutil reset Camera' in Terminal with admin privileges")
+                sys.exit(1)
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/src/tool_use/utils/config_wizard.py b/src/tool_use/utils/config_wizard.py
index 024ba82..cecd830 100644
--- a/src/tool_use/utils/config_wizard.py
+++ b/src/tool_use/utils/config_wizard.py
@@ -34,6 +34,20 @@
                 "default": "tiny.en",
             }
         }
+    },
+    "posture": {
+        "name": "Posture Coach",
+        "description": "Monitor posture and focus using AI and webcam",
+        "config_keys": {
+            "capture_interval": {
+                "description": "Interval between captures in seconds",
+                "default": 10,
+            },
+            "save_images": {
+                "description": "Save captured images to disk",
+                "default": False,
+            }
+        }
     }
 }