near-ai

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NEAR AI agent development and integration. Use when building AI agents on NEAR, integrating AI models, creating agent workflows, or implementing AI-powered dApps on NEAR Protocol.

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Sourcenear/agent-skills

Added on2026-02-07

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npx skill4agent add near/agent-skills near-ai

SKILL.md Content

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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


arch-
ai-
comm-
model-
workflow-
security-
best-

Priority	Category	Impact	Prefix
1	Agent Architecture	CRITICAL	`arch-`
2	AI Integration	HIGH	`ai-`
3	Agent Communication	HIGH	`comm-`
4	Model Deployment	MEDIUM-HIGH	`model-`
5	Agent Workflows	MEDIUM	`workflow-`
6	Security & Privacy	MEDIUM	`security-`
7	Best Practices	MEDIUM	`best-`

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