🤖 AI Agent Contract Enforcement System
A structured engineering framework for designing, validating, and enforcing Prompt Contracts in LLM-powered AI agent systems.
This project introduces a contract-based architecture that ensures:
✅ Structured Outputs
✅ Behavioral Consistency
✅ Safety & Guardrails
✅ Failure Detection & Recovery
✅ Ethical Boundary Enforcement
✅ Production-Level Reliability
📌 Problem Statement
Modern LLM-based agents often suffer from:
Unstructured outputs
Prompt drift
Instruction leakage
Safety violations
Inconsistent reasoning
Hallucinated responses
Non-deterministic behavior
Traditional prompt engineering is not enough for production systems.
We need Prompt Contract Engineering.
🏗️ What is Prompt Contract Engineering?
Prompt Contract Engineering defines a formal agreement between:
🧠 The AI Agent
👤 The User
⚙️ The System
A Prompt Contract specifies:
Role definition
Input schema
Output schema
Constraints
Safety boundaries
Allowed tools
Failure handling rules
Escalation conditions
The agent must comply with the contract before producing output.
🧱 System Architecture User Input │ ▼ Contract Validator │ ▼ Prompt Constructor │ ▼ LLM Agent │ ▼ Output Schema Validator │ ├── Valid → Response Delivered └── Invalid → Retry / Repair / Escalate 📂 Project Structure AI-Agent-Contract-Enforcement-System/ │ ├── contracts/ │ ├── base_contract.yaml │ ├── medical_agent_contract.yaml │ └── financial_agent_contract.yaml │ ├── core/ │ ├── contract_validator.py │ ├── schema_enforcer.py │ ├── safety_guardrails.py │ └── retry_mechanism.py │ ├── examples/ │ ├── medical_diagnosis_agent.ipynb │ └── structured_reasoning_demo.ipynb │ ├── tests/ │ └── contract_violation_tests.py │ └── README.md 🔐 Key Features 1️⃣ Role Enforcement
Defines strict agent identity and prevents prompt injection.
2️⃣ Structured Output Contracts
Enforces JSON schema validation for deterministic outputs.
Example:
{ "risk_level": "low | medium | high", "confidence_score": 0.0 - 1.0, "explanation": "string", "recommended_action": "string" } 3️⃣ Guardrail Layer
Toxicity filtering
Domain restriction
Ethical boundary enforcement
Sensitive content blocking
4️⃣ Failure Handling Mechanism
Output repair
Auto-retry with constraint reminder
Escalation to human review
Logging of violations
5️⃣ Contract Violation Detection
Detects:
Schema mismatch
Missing required fields
Safety boundary breach
Uncertainty threshold violation
🧪 Example Use Cases
🏥 Medical Decision Support Agents
📊 Financial Risk Assessment Bots
⚖️ Ethical AI Simulation Systems
🛡️ AI Incident Response Agents
🧠 Autonomous Research Agents