OpenClaw Best Practices - Skill Development

Overview

Skill Architecture

Skill Lifecycle

Discovery → Loading → Initialization → Matching → Execution → Result Return
  ↓         ↓          ↓              ↓          ↓           ↓
Auto-scan  Lazy-load  Config Validation Intent Matching Sandbox Execution Formatted Output

Skill Structure

my-skill/
├── index.ts          # Skill Entry Point
├── config.schema.json # Configuration Schema
├── README.md         # Usage Instructions
├── tests/            # Test Files
│   └── skill.test.ts
└── package.json      # Dependency Management

Development Standards

1. Skill Definition

• Name: Unique identifier
• Description: Used for AI intent matching
• Parameter Schema: JSON Schema for input parameters
• Permission Declaration: Required system permissions
• Return Format: Output data structure

2. Code Standards

3. Security Standards

• Least Privilege: Request only necessary permissions
• Input Validation: Validate all user inputs
• Output Sanitization: Prevent sensitive information leakage
• Dependency Audit: Regularly check dependency security
• Sandbox Compatibility: Ensure it runs in a sandbox environment

4. Performance Standards

• Startup time < 100ms
• Execution timeout defaults to 30 seconds
• Memory usage < 50MB
• Support cancellation
• Results can be cached

Common Skill Patterns

Pattern 1: API Call Type

Suitable for skills calling external APIs

Input → Parameter Construction → API Call → Response Parsing → Formatted Output

Pattern 2: Data Processing Type

Suitable for data analysis and transformation

Input → Data Acquisition → Processing/Analysis → Result Generation → Return

Pattern 3: Interactive Type

Suitable for skills requiring multi-turn interaction

Initial Request → Confirmation/Additional Information → Execution → Feedback → Completion

Pattern 4: Monitoring Type

Suitable for continuous monitoring skills

Configure Trigger Conditions → Periodic Check → Condition Met → Trigger Notification

Testing Strategy

Release Process

1. Development: Local development and testing
2. Self-Review: Code quality and security checks
3. Documentation: Write README and usage examples
4. Submission: Submit to the skill marketplace for review
5. Review: Community security audit
6. Release: Publish after approval

Conclusion

High-quality skill development is the foundation of OpenClaw's ecosystem prosperity. Following security, performance, and code standards, and writing skills with test coverage, are the best practices for every OpenClaw developer.

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*Analysis Date: March 28, 2026*