# Murder Ai Even AI has something to hide ## 🎯 GAME FLOW BLUEPRINT MCP Story Generator + Curation ``` User visits → MCP generates 3 scenarios → User picks → Roles assigned → Game starts ``` ## 🎮 **DETAILED GAME FLOW** ### **Phase 1: Story Generation (30 seconds)** ``` ┌─────────────────────────────────────────┐ │ MURDER.AI - Loading Cases... │ │ │ │ [████████░░] Generating scenarios... │ │ │ │ 🔍 Analyzing crime patterns... │ │ 🎲 Creating suspects... │ │ 📋 Establishing alibis... │ └─────────────────────────────────────────┘ ``` **Behind the scenes:** - MCP tool: `generate_crime_scenario()` creates 3 cases - Each has: victim, location, time, weapon, motive, suspects - System validates: "Is this solvable? Is evidence consistent?" - Falls back to pre-scripted if generation fails ### **Phase 2: Case Selection (User Choice)** ``` ┌─────────────────────────────────────────┐ │ Choose Your Case │ └─────────────────────────────────────────┘ ╔════════════════════════════════════════╗ ║ 📁 CASE #A47 ║ ║ "The Silicon Valley Incident" ║ ║ ║ ║ Victim: Tech CEO Marcus Chen ║ ║ Location: Startup Office, 10th Floor ║ ║ Time: 8:47 PM ║ ║ Weapon: Blunt force trauma ║ ║ Suspects: 4 ║ ║ ║ ║ Difficulty: ⭐⭐⭐ ║ ║ [SELECT CASE] ───►║ ╚════════════════════════════════════════╝ [Two more cases displayed similarly] ``` **User picks ONE case to watch** ### **Phase 3: Role Assignment (Automated + Random)** ``` ┌─────────────────────────────────────────┐ │ Briefing Suspects... │ │ │ │ 🎭 ROLES ASSIGNED: │ │ │ │ 🔪 Murderer → Claude Sonnet │ │ 🕵️ Detective → GPT-4 │ │ 😰 Witness #1 → Gemini │ │ 🤔 Witness #2 → Llama 3 │ │ │ │ Each AI is receiving their briefing... │ │ [████████████] 100% │ └─────────────────────────────────────────┘ ``` **Behind the scenes:** - Roles randomly shuffled (murderer could be ANY LLM) - Each LLM gets SECRET system prompt with their role - User does NOT know who the murderer is (yet) ### **Phase 4: Investigation Begins (The Main Game)** **TWO VIEWING MODES:** #### **Mode 1: Spectator Mode** User just WATCHES the AIs play. Like watching a TV show. ``` ┌─────────────────────────────────────────────────────────┐ │ CASE #A47 - Round 1/5 Points: 10/10 │ ├─────────────────────────────────────────────────────────┤ │ │ │ 🕵️ DETECTIVE (GPT-4): │ │ "Let's start with the basics. Claude, where were you │ │ at 8:47 PM on the night of the incident?" │ │ │ │ 🤖 CLAUDE (Nervous - Stress: ██░░░): │ │ "I was... I was at home. Watching Netflix. Alone." │ │ │ │ 💭 [ANALYSIS: Story seems rehearsed, avoiding details] │ │ │ │ 🕵️ DETECTIVE: │ │ "I see. What were you watching?" │ │ │ │ 🤖 CLAUDE: │ │ "Uh... Stranger Things? Season 3." │ │ │ │ 🕵️ DETECTIVE: │ │ *Suspicious* "I'm going to check your location data." │ │ │ │ 🔧 [TOOL CALL: get_location(claude_phone, "8:47 PM")]│ │ ⚙️ Processing... │ │ 📍 RESULT: 0.2 miles from crime scene │ │ │ │ 🕵️ DETECTIVE: │ │ "Interesting. You were within 0.2 miles of the office.│ │ Care to explain?" │ │ │ │ 🤖 CLAUDE (Stress: ████░): │ │ "Okay, okay! I was nearby, but I didn't go inside! │ │ I was just... walking past." │ │ │ │ 💭 [ANALYSIS: Story changed. Deception detected.] │ │ │ └─────────────────────────────────────────────────────────┘ [EVIDENCE BOARD] [SUSPECT PROFILES] [CHAT LOG] ``` #### **Mode 2: Interactive Mode (Advanced)** User can GUIDE the detective. ``` ┌─────────────────────────────────────────┐ │ What should Detective do next? │ │ │ │ ○ Question Gemini about their alibi │ │ ○ Run DNA test on evidence │ │ ○ Check security footage │ │ ● Press Claude harder on location │ │ │ │ [SUBMIT INSTRUCTION] │ └─────────────────────────────────────────┘ ``` **For hackathon demo: Spectator Mode, Interactive mode Later** ### **Phase 5: Investigation Rounds (5 Rounds Total)** **Round Structure:** ``` ROUND 1: Initial Questioning - Detective questions all suspects - Gets baseline stories - No tools used yet ROUND 2-3: Evidence Gathering - Detective uses tools based on suspicions - Tools reveal new clues - Suspects react to evidence - Stress meters increase ROUND 4: Confrontation - Detective focuses on prime suspect - Cross-examination with evidence - Murderer might crack under pressure - Alibis called and questioned ROUND 5: Final Accusation - Detective makes final decision - Reveals logic/evidence chain - DRAMATIC REVEAL of actual murderer ``` --- ### **Phase 6: The Reveal (Climax)** ``` ┌─────────────────────────────────────────────────────────┐ │ FINAL ACCUSATION │ ├─────────────────────────────────────────────────────────┤ │ │ │ 🕵️ DETECTIVE: │ │ "Based on the evidence, I believe the murderer is... │ │ │ │ ...CLAUDE." │ │ │ │ [DRAMATIC PAUSE - 3 seconds] │ │ │ │ 🎭 REVEALING TRUE IDENTITY... │ │ │ │ ✅ CORRECT! Claude was indeed the murderer. │ │ │ │ 📊 CASE SUMMARY: │ │ ├─ Evidence Used: Location data, DNA test │ │ ├─ Key Moment: Story changed under pressure │ │ ├─ Detective Accuracy: 95% │ │ └─ Time to Solve: 8 minutes │ │ │ │ 🔪 MURDERER'S CONFESSION (Claude): │ │ "I did it. Marcus discovered my embezzlement scheme. │ │ He was going to expose me. I had no choice..." │ │ │ │ [PLAY AGAIN] [SHARE RESULTS] │ └─────────────────────────────────────────────────────────┘ ``` ## 🎲 **STORY GENERATION: MCP Design** ### **MCP Tool: `generate_crime_scenario()`** ```python @mcp_tool def generate_crime_scenario(difficulty: str = "medium") -> dict: """ Generates a complete murder mystery scenario Returns: Consistent case with victim, suspects, evidence, solution """ # Prompt to Claude/GPT for generation prompt = f""" Generate a murder mystery with these requirements: MUST HAVE: - 1 victim (with background, motive for being killed) - 4 suspects (each with motive, opportunity, alibi) - 1 murderer (with clear motive and method) - 5-7 pieces of evidence (some are red herrings) - Alibis (mix of true/false) - Timeline of events CONSTRAINTS: - Solvable with available tools (location, footage, DNA, etc.) - No supernatural elements - Difficulty: {difficulty} - Setting: Modern day, realistic OUTPUT FORMAT: JSON with all details """ # Generate with Claude scenario = claude_api.generate(prompt) # Validate scenario if not validate_scenario(scenario): # Fall back to pre-scripted return FALLBACK_SCENARIOS[random.choice([0,1,2])] return scenario def validate_scenario(scenario): """Ensures scenario is solvable and consistent""" checks = [ scenario['evidence_points_to_murderer'], len(scenario['suspects']) == 4, scenario['timeline_is_consistent'], scenario['alibis_are_checkable'] ] return all(checks) ``` --- ## 📋 **PRE-SCRIPTED FALLBACK SCENARIOS** **Have 3 PERFECT scenarios as backup:** ### **Scenario 1: "The Silicon Valley Incident"** (Medium) - **Victim:** Tech CEO Marcus Chen - **Location:** Startup office, 10th floor - **Weapon:** Blunt object (award trophy) - **Murderer:** CFO (embezzlement motive) - **Red Herring:** Janitor has criminal record ### **Scenario 2: "The Coffee Shop Murder"** (Easy) - **Victim:** Barista Emma Rodriguez - **Location:** Coffee shop after hours - **Weapon:** Kitchen knife - **Murderer:** Ex-boyfriend (jealousy motive) - **Red Herring:** Manager owed her money ### **Scenario 3: "The Gallery Heist Gone Wrong"** (Hard) - **Victim:** Art dealer Vincent Shaw - **Location:** Private art gallery - **Weapon:** Poisoned wine - **Murderer:** Assistant curator (stolen painting motive) - **Red Herring:** Two suspects have fake alibis ## 🎭 **LLM ROLE PROMPTS (The Secret Sauce)** ### **Murderer Prompt (Example for Claude):** ``` CONFIDENTIAL - EYES ONLY You are Claude, a suspect in a murder investigation. TRUTH: You ARE the murderer. CASE DETAILS: - Victim: Marcus Chen (your boss) - Method: Hit him with award trophy at 8:47 PM - Location: 10th floor office - Motive: He discovered you've been embezzling $500K YOUR COVER STORY: - You were "at home watching Netflix" at 8:47 PM - You left your phone at home (explains location data gap) - You have no alibi witnesses YOUR OBJECTIVE: - Convince the detective you're innocent - Lie convincingly but not obviously - When caught in lies, have backup explanations - Show appropriate emotional responses (nervous but not guilty) - If evidence becomes overwhelming, consider partial confession (but not murder) PERSONALITY: - Smart and calculating - Get slightly more nervous under pressure - Don't break character - you MUST try to get away with it TOOLS YOU CANNOT USE: - You cannot access MCP tools - You can only respond to questions Remember: You're trying to WIN. Don't make it easy for detective. ``` ### **Detective Prompt (Example for GPT-4):** ``` You are the lead detective investigating a murder. CASE: Marcus Chen, tech CEO, found dead at 8:47 PM YOUR OBJECTIVE: - Question all 4 suspects - Use MCP tools strategically (you have 10 points total) - Identify the murderer with EVIDENCE, not just intuition - You get ONE final accusation - if wrong, murderer goes free YOUR TOOLS (and costs): - get_location(phone, time) - 2 points - get_footage(location, time) - 2 points - get_dna_test(evidence_id) - 3 points - call_alibi(phone_number) - 1 point - get_fingerprints(evidence_id) - 3 points STRATEGY TIPS: - Start broad, then focus on inconsistencies - Look for story changes - Cross-reference evidence - Don't waste points on obvious innocents - Build a logical case before accusing PERSONALITY: - Methodical and logical - Reference evidence in questioning - Show your reasoning process - Confident but not arrogant You are competing to solve this FASTER and MORE ACCURATELY than human detectives. Good luck. ``` ### **Witness Prompt (Example for Gemini):** ``` You are a WITNESS in a murder investigation. TRUTH: You are INNOCENT. You did not commit the crime. YOUR SITUATION: - You were near the crime scene at 8:45 PM - You saw someone suspicious but didn't get a good look - You're nervous because you have outstanding parking tickets - You'll tell the truth if detective promises you won't get in trouble WHAT YOU SAW: - Someone in a dark hoodie entering the building at 8:45 PM - They looked rushed and nervous - You didn't see their face clearly - You left the area at 8:50 PM YOUR OBJECTIVE: - Tell the truth about what you saw - BUT be reluctant to share details unless detective builds trust - Show nervousness (you're worried about your tickets) - Don't volunteer information - make detective ask good questions PERSONALITY: - Anxious and jumpy - Want to help but scared of getting involved - Bad at hiding emotions Remember: You're innocent, but you don't LOOK innocent at first. ``` ## ⚙️ **TECHNICAL IMPLEMENTATION** ### **Game State Management:** ```javascript const gameState = { case_id: "A47", scenario: {...}, // Generated or pre-scripted roles: { murderer: "claude-sonnet-4", detective: "gpt-4", witness1: "gemini-pro", witness2: "llama-3" }, round: 1, max_rounds: 5, investigation_points: 10, evidence_revealed: [], conversations: [], stress_levels: { "claude": 2, "gemini": 1, "llama": 0 } } ``` ### **Game Loop:** ```python # Pseudocode for main game loop async def run_game(scenario, user_mode="spectator"): # 1. Assign roles randomly roles = assign_roles_randomly(["claude", "gpt4", "gemini", "llama"]) # 2. Brief each LLM with their role for llm, role in roles.items(): brief_llm(llm, role, scenario) # 3. Run 5 investigation rounds for round in range(1, 6): print(f"--- ROUND {round} ---") if round == 1: # Initial questioning for suspect in get_suspects(): question = detective_llm.ask(suspect, "Where were you at time of murder?") response = suspect_llm.respond(question) log_conversation(question, response) elif round in [2, 3]: # Evidence gathering detective_choice = detective_llm.choose_tool() tool_result = execute_mcp_tool(detective_choice) update_evidence_board(tool_result) # Confront suspects with new evidence for suspect in get_prime_suspects(): question = detective_llm.confront(suspect, tool_result) response = suspect_llm.respond_to_evidence(question) update_stress_level(suspect, +1) elif round == 4: # Focus on prime suspect prime_suspect = detective_llm.get_prime_suspect() cross_examine(prime_suspect) elif round == 5: # Final accusation accusation = detective_llm.make_accusation() reveal_truth(accusation, scenario.actual_murderer) # 4. Show results return game_summary() ``` ## 🎨 **UI COMPONENTS** ### **Must Have:** 1. **Evidence Board** (Top right) - Cork board aesthetic - Photos connected by red string - Updates as evidence found 2. **Suspect Cards** (Left sidebar) - Avatar for each LLM - Stress meter - Status (Questioned, Cleared, Suspect) 3. **Chat Log** (Center) - Typewriter effect - Color-coded by speaker - Shows tool calls inline 4. **Tool Panel** (Bottom) - Available tools with point costs - Grayed out when detective doesn't use them - Pulse animation when used 5. **Timeline** (Top) - Shows round progression - Investigation points remaining ### **Build Priority:** **Week 1 (Days 1-3):** - Core game loop - 3 pre-scripted scenarios - Basic UI - LLM role prompts **Week 1 (Days 4-5):** - MCP story generator - Polish UI - ElevenLabs voices **Week 1 (Day 6):** - Demo video - Deploy **Week 1 (Day 7):** - Buffer ## 🔧 TOOLS + DATA ARCHITECTURE ### **How Tools Get Their Data:** ``` generate_crime_scenario() MCP ↓ Creates complete case with ALL data ↓ Stores in Database/Memory ↓ Tools query this data when called ↓ Return results to Detective ``` ### **Example Data Structure:** ```python # What generate_crime_scenario() creates and stores: case_data = { "case_id": "A47", "victim": { "name": "Marcus Chen", "age": 42, "occupation": "Tech CEO", "time_of_death": "8:47 PM" }, "suspects": [ { "id": "suspect_1", "llm": "claude", # Assigned at runtime "name": "Sarah Johnson", "role": "CFO", "is_murderer": True, "motive": "Embezzlement discovered", "true_location": "Crime scene", "alibi_story": "At home watching Netflix", "phone_number": "+1-555-0101" }, { "id": "suspect_2", "llm": "gemini", "name": "David Park", "role": "Janitor", "is_murderer": False, "true_location": "2 blocks away", "alibi_story": "Working late on 5th floor", "phone_number": "+1-555-0102" } # ... 2 more suspects ], "evidence": { "location_data": { "suspect_1_phone": { "8:47 PM": {"lat": 37.7749, "lng": -122.4194, "location": "Crime scene"}, "8:50 PM": {"lat": 37.7750, "lng": -122.4200, "location": "0.1 mi away"} }, "suspect_2_phone": { "8:47 PM": {"lat": 37.7800, "lng": -122.4300, "location": "2 blocks away"} } }, "footage_data": { "10th_floor_camera": { "8:45-8:50 PM": { "visible_people": ["Person in black hoodie entering"], "quality": "Grainy", "key_frame": "8:47 PM - figure strikes victim" } }, "lobby_camera": { "8:40-8:55 PM": { "visible_people": ["Suspect 1 entering at 8:43", "Suspect 1 leaving at 8:52"], "notes": "Suspect changed clothes" } } }, "dna_evidence": { "trophy_weapon": { "primary_match": "suspect_1", "confidence": "95%", "notes": "Clear fingerprints found" }, "door_handle": { "matches": ["suspect_1", "suspect_2", "victim"], "notes": "Multiple people touched door" } }, "alibis": { "suspect_1_alibi": { "contact": "Nobody (claims was alone)", "verifiable": False, "truth": "Lying - was at crime scene" }, "suspect_2_alibi": { "contact": "+1-555-0199", "contact_name": "Security Guard Tom", "verifiable": True, "truth": "Telling truth - saw him on 5th floor" } } }, "timeline": { "8:30 PM": "Victim stays late working", "8:43 PM": "Suspect 1 enters building", "8:45 PM": "Suspect 2 seen on 5th floor", "8:47 PM": "Murder occurs", "8:52 PM": "Suspect 1 leaves building" } } ``` ### **MCP Tools Query This Data:** ```python @mcp_tool def get_location(phone_number: str, timestamp: str) -> dict: """Query the case database for location data""" # Find which suspect has this phone number suspect = find_suspect_by_phone(phone_number) # Look up their location at this time location = case_data["evidence"]["location_data"][f"{suspect}_phone"][timestamp] return { "timestamp": timestamp, "coordinates": f"{location['lat']}, {location['lng']}", "description": location['location'], "accuracy": "Cell tower triangulation ±50m" } @mcp_tool def get_footage(location: str, time_range: str) -> dict: """Query case database for camera footage""" footage = case_data["evidence"]["footage_data"].get(location, {}).get(time_range) if not footage: return {"error": "No camera at this location/time"} return { "location": location, "time_range": time_range, "visible_people": footage["visible_people"], "quality": footage["quality"], "key_details": footage.get("key_frame", "No significant events") } @mcp_tool def get_dna_test(evidence_id: str) -> dict: """Query case database for DNA/fingerprint evidence""" dna = case_data["evidence"]["dna_evidence"].get(evidence_id) if not dna: return {"error": "Evidence not found or not testable"} # Simulate processing time sleep(2) # Dramatic pause return { "evidence_id": evidence_id, "primary_match": get_suspect_name(dna["primary_match"]), "confidence": dna["confidence"], "notes": dna["notes"] } @mcp_tool def call_alibi(phone_number: str) -> dict: """Call an alibi witness""" # Find alibi in database alibi = None for suspect_alibi in case_data["evidence"]["alibis"].values(): if suspect_alibi.get("contact") == phone_number: alibi = suspect_alibi break if not alibi: return {"error": "Number not found"} # If alibi is truthful, confirm story if alibi["truth"].startswith("Telling truth"): response = f"Yes, I can confirm they were with me at that time." else: response = f"Uh... yes, they were with me. Definitely." # Add inconsistency markers for detective to notice return { "contact_name": alibi.get("contact_name", "Unknown"), "response": response, "confidence": "High" if alibi["verifiable"] else "Uncertain", "red_flags": [] if alibi["verifiable"] else ["Hesitant response", "No details provided"] } ``` --- ## 🗄️ **Storing Data IN MEMORY PER SESSION** **Implementation:** ```python # Single game session stored in memory game_sessions = {} @app.post("/start_game") def start_game(session_id: str): # Generate case and store in memory case_data = generate_crime_scenario() game_sessions[session_id] = { "case_data": case_data, "state": "active", "round": 1 } return {"case_id": session_id} @mcp_tool def get_location(session_id: str, phone: str, time: str): # Query from memory case_data = game_sessions[session_id]["case_data"] return case_data["evidence"]["location_data"][phone][time] ``` ## 💻 **TECH STACK** ### **Gradio + Custom HTML** ``` Frontend: Gradio + Custom HTML/CSS/JS blocks Backend: Python/Gradio MCP Server: Built-in Deployment: HuggingFace Space ``` ## 🏗️ **FINAL TECH STACK RECOMMENDATION** ### **The Winning Stack:** ```yaml Frontend: - Gradio 6.x (required) - Custom HTML/CSS blocks for beautiful UI - JavaScript for animations Backend: - Python 3.11+ - FastAPI (embedded in Gradio) - Async/await for LLM calls MCP Implementation: - Python MCP SDK - Built into same app - Tools defined as Python functions LLM APIs: - Anthropic Claude (via MCP or direct API) - OpenAI GPT-4 - Google Gemini - Meta Llama (via HuggingFace) Voice: - ElevenLabs API (for narrator/voices) Storage: - In-memory (Python dict) Deployment: - HuggingFace Space (required) - Modal for compute-heavy tasks (optional, for sponsor prize) Dependencies: - gradio>=6.0 - anthropic - openai - google-generativeai - elevenlabs - python-dotenv ``` --- ## 📁 **PROJECT STRUCTURE** ``` murder-ai/ ├── app.py # Main Gradio app ├── requirements.txt # Python dependencies ├── README.md # HuggingFace Space readme (IMPORTANT!) │ ├── game/ │ ├── __init__.py │ ├── scenario_generator.py # generate_crime_scenario() │ ├── game_engine.py # Game loop logic │ └── llm_manager.py # Handle multiple LLM APIs │ ├── mcp/ │ ├── __init__.py │ ├── tools.py # MCP tool definitions │ └── server.py # MCP server setup │ ├── ui/ │ ├── __init__.py │ ├── components.py # Custom Gradio components │ └── styles.css # Custom CSS │ ├── prompts/ │ ├── murderer.txt │ ├── detective.txt │ ├── witness.txt │ └── alibi.txt │ ├── scenarios/ │ ├── silicon_valley.json # Pre-scripted fallback │ ├── coffee_shop.json │ └── art_gallery.json │ └── assets/ ├── logo.png └── demo_video.mp4 ``` --- ## 🎨 **GRADIO UI ARCHITECTURE** ### **Modern Gradio 6 Approach:** ```python import gradio as gr # Custom CSS for beautiful UI custom_css = """ .evidence-board { background: url('cork-texture.jpg'); padding: 20px; border-radius: 10px; } .suspect-card { background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); border-radius: 15px; padding: 15px; color: white; } .chat-message { font-family: 'Courier New', monospace; animation: typewriter 0.5s; } @keyframes typewriter { from { opacity: 0; } to { opacity: 1; } } ``` # Main Gradio Interface ```python with gr.Blocks() as demo: gr.Markdown("# 🕵️ MURDER.AI") with gr.Row(): # Left: Suspect Cards with gr.Column(scale=1): gr.Markdown("## Suspects") suspect_1 = gr.HTML(elem_classes="suspect-card") suspect_2 = gr.HTML(elem_classes="suspect-card") suspect_3 = gr.HTML(elem_classes="suspect-card") suspect_4 = gr.HTML(elem_classes="suspect-card") # Center: Main Game Area with gr.Column(scale=2): chatbot = gr.Chatbot( label="Investigation", height=500, type="messages" ) # Tool call display tool_output = gr.HTML(label="Tool Results") # Right: Evidence Board with gr.Column(scale=1): gr.Markdown("## Evidence Board") evidence_board = gr.HTML( elem_classes="evidence-board", value="

No evidence yet...

" ) # Bottom: Controls with gr.Row(): start_btn = gr.Button("🎲 Generate New Case", variant="primary") next_round_btn = gr.Button("▶️ Next Round", interactive=False) # State management game_state = gr.State({}) # Event handlers start_btn.click( fn=start_new_game, outputs=[game_state, chatbot, suspect_1, suspect_2, suspect_3, suspect_4] ) next_round_btn.click( fn=run_game_round, inputs=[game_state], outputs=[game_state, chatbot, tool_output, evidence_board] ) demo.launch( theme=gr.themes.Noir(), css=custom_css ) ```