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creating-agents

Create and test AI agents using a Test-Driven Development approach.

Updated Feb 12, 2026
Search Tags:#testing#tdd#prompt engineering#ai agents#agent development#scope enforcement
One-click install
npx skills add https://github.com/othercode/profiles --skill creating-agents-othercode
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: creating-agents
Source: https://github.com/othercode/profiles/tree/main/plugins/prompt-engineering/skills/creating-agents
Command: npx skills add https://github.com/othercode/profiles --skill creating-agents-othercode

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive framework and methodology for creating, testing, and refining AI agents, ensuring they are robust, well-defined, and adhere to their intended scope.

Core Features & Use Cases

  • Test-Driven Development (TDD) for Agents: Apply the RED-GREEN-REFACTOR cycle to agent creation.
  • Scope Enforcement: Detailed guidance on defining and enforcing agent boundaries using CRITICAL rules.
  • Testing Methodologies: Covers delegation, behavior, and boundary testing with practical scenarios.
  • Use Case: When developing a new agent for code analysis, use this Skill to guide the entire process from initial concept to a bulletproof, production-ready agent that never oversteps its bounds.

Quick Start

Use the creating-agents skill to follow the TDD methodology for building a new AI agent.

Frequently Asked Questions about creating-agents

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build AI agents with test-driven development?▼

Apply the RED-GREEN-REFACTOR cycle to agent creation to build AI agents with test-driven development, ensuring robust roles and rigorous behavior testing throughout the process.

What is scope enforcement in AI agent development?▼

Scope enforcement in AI agent development is defining and enforcing agent boundaries using CRITICAL rules to ensure specialized assistants never overstep their intended operational limits.

How do I test AI agent boundaries and delegation behavior?▼

Test AI agent boundaries and delegation behavior by implementing practical testing scenarios that verify boundary adherence and delegation, ensuring the agent remains within its defined scope.

When do I need to use CRITICAL rules for AI agents?▼

Use CRITICAL rules for AI agents when you need to enforce strict scope boundaries, ensuring your specialized assistant adheres to its intended role and never oversteps its operational bounds.

What is the best way to create specialized AI assistants?▼

The best way to create specialized AI assistants is following a comprehensive TDD methodology that guides the process from initial concept to a bulletproof, production-ready agent.

Can I use TDD methodology for production-ready AI agent development?▼

Yes, you can use TDD methodology for production-ready AI agent development, applying the RED-GREEN-REFACTOR cycle to ensure your agent is robust, well-defined, and adheres to its intended scope.

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