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agent-creator

Generate enterprise AI agent system prompts with XML contract structures.

3|3|Updated Mar 5, 2026
Search Tags:#SDLC#XML#system-prompt#JSON-schema#agent-creator#enterprise-standards
One-click install
npx skills add https://github.com/webdevcom01-cell/agent-studio --skill agent-creator-webdevcom01-cell
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-creator
Source: https://github.com/webdevcom01-cell/agent-studio/tree/main/.claude/skills/agent-creator
Command: npx skills add https://github.com/webdevcom01-cell/agent-studio --skill agent-creator-webdevcom01-cell

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enterprise teams need to produce production-ready system prompts for AI agents that meet 2026 standards, ensuring consistency, safety, and deployability.

Core Features & Use Cases

  • Generates complete system prompts with all required sections: <role>, <output_format>, <constraints>, <failure_modes>, and <example> blocks.
  • Enforces crisp agent identity, verifiable output contracts, hard constraints, and explicit failure modes.
  • Supports multi-language prompts and can be adapted for both leaf and orchestrator agents in enterprise pipelines.

Quick Start

Provide a project description for an enterprise agent and this skill will generate a production-ready system prompt following the 2026 standard.

Frequently Asked Questions about agent-creator

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

FAQPage Schema
How do I create a production-ready system prompt for an enterprise AI agent?▼

The 2026 contract-first standard requires system prompts to include specific XML blocks. This skill automatically generates the mandatory <role>, <output_format>, <constraints>, <failure_modes>, and <example> sections to ensure your agent meets enterprise compliance standards.

How do I define an AI agent's role and output contract using JSON schema?▼

This skill generates system prompts for both leaf and orchestrator agents. It defines crisp role identities and verifiable output contracts using a formal XML and JSON structure, making it suitable for complex multi-agent enterprise pipelines.

What is the best way to structure failure modes and constraints in AI agent prompts?▼

This skill supports multi-language prompt generation. You can adapt the generated prompts for both leaf and orchestrator agents, ensuring your enterprise system prompts meet the 2026 Anthropic and Google DeepMind contract-first standards across different languages.

Can I use this approach to build both leaf and orchestrator agents for enterprise pipelines?▼

Enterprise system prompts need explicit failure modes and hard constraints to ensure safety and deployability. This skill automatically includes <failure_modes> and <constraints> XML blocks, preventing unpredictable agent behavior in production environments.

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