NEAR AI Development

Comprehensive guide for building AI agents and AI-powered applications on NEAR Protocol, including NEAR AI integration, agent workflows, and AI model deployment.

When to Apply

Reference these guidelines when:

• Building AI agents on NEAR
• Integrating AI models with NEAR smart contracts
• Creating agent-based workflows
• Implementing AI-powered dApps
• Using NEAR AI infrastructure
• Building with NEAR AI Assistant

Rule Categories by Priority

Quick Reference

1. Agent Architecture (CRITICAL)

• arch-agent-structure – Design modular agent architecture
• arch-state-management – Manage agent state on-chain vs off-chain
• arch-agent-registry – Register agents in NEAR AI registry
• arch-composability – Build composable agents
• arch-agent-capabilities – Define clear agent capabilities

2. AI Integration (HIGH)

• ai-model-selection – Choose appropriate AI models
• ai-inference-endpoints – Use NEAR AI inference endpoints
• ai-prompt-engineering – Design effective prompts for agents
• ai-context-management – Manage conversation context
• ai-response-validation – Validate and sanitize AI responses

3. Agent Communication (HIGH)

• comm-agent-protocol – Implement standard agent communication protocols
• comm-message-format – Use structured message formats
• comm-async-messaging – Handle asynchronous agent communication
• comm-multi-agent – Coordinate multiple agents
• comm-human-in-loop – Implement human-in-the-loop patterns

4. Model Deployment (MEDIUM-HIGH)

• model-hosting – Deploy models on NEAR AI infrastructure
• model-versioning – Version and update AI models
• model-optimization – Optimize models for inference
• model-monitoring – Monitor model performance
• model-fallbacks – Implement fallback strategies

5. Agent Workflows (MEDIUM)

• workflow-task-planning – Implement agent task planning
• workflow-execution – Execute multi-step workflows
• workflow-error-handling – Handle workflow errors gracefully
• workflow-state-persistence – Persist workflow state
• workflow-composability – Compose workflows from smaller tasks

6. Security & Privacy (MEDIUM)

• security-input-validation – Validate user inputs to agents
• security-output-sanitization – Sanitize agent outputs
• security-access-control – Implement agent access control
• security-data-privacy – Protect user data privacy
• security-prompt-injection – Prevent prompt injection attacks

7. Best Practices (MEDIUM)

• best-error-messages – Provide clear error messages
• best-logging – Log agent interactions for debugging
• best-testing – Test agent behavior comprehensively
• best-documentation – Document agent capabilities and APIs
• best-user-feedback – Collect and incorporate user feedback

How to Use

Read individual rule files for detailed explanations and code examples:

rules/arch-agent-structure.md
rules/ai-inference-endpoints.md

Each rule file contains:

• Brief explanation of why it matters
• Incorrect code example with explanation
• Correct code example with explanation
• Additional context and NEAR AI-specific patterns

NEAR AI Components

NEAR AI Hub

Central registry for AI agents, models, and datasets on NEAR.

NEAR AI Assistant

Infrastructure for building conversational AI agents.

Agent Registry

On-chain registry for discovering and interacting with agents.

Inference Endpoints

Decentralized inference infrastructure for AI models.

Resources

• NEAR AI Documentation: https://docs.near.ai/
• NEAR AI Hub: https://app.near.ai/
• NEAR AI GitHub: https://github.com/near/nearai
• Agent Examples: https://github.com/near/nearai/tree/main/examples
• NEAR AI Research: https://near.ai/research

Full Compiled Document

For the complete guide with all rules expanded: AGENTS.md