agent-creator

Generate sub-agent Markdown configuration files with YAML frontmatter from user descriptions.

18|1|Updated Nov 5, 2015

Search Tags:#automation #agent #configuration #Markdown #frontmatter #sub-agent

Ready to run

npx skills add https://github.com/cristianoliveira/dotfiles --skill agent-creator-cristianoliveira

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-creator
Source: https://github.com/cristianoliveira/dotfiles/tree/main/ai/shared/skills/agent-creator
Command: npx skills add https://github.com/cristianoliveira/dotfiles --skill agent-creator-cristianoliveira

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the creation of sub-agent configuration files from user descriptions, enabling rapid, consistent agent definitions without manual drafting.

Core Features & Use Cases

Markdown-based agent configuration: Generates a complete Markdown file with YAML frontmatter for new sub-agents.
Guided requirements gathering: Provides a structured workflow to collect purpose, tasks, and tools for the agent.
Use Case: A product team quickly prototypes a "data-cleaner" sub-agent to handle data wrangling tasks in an automation pipeline.

Quick Start

Provide a user description of the desired sub-agent and any constraints, and the system will generate ai/shared/agents/<name>.md with frontmatter and a detailed workflow.

Frequently Asked Questions about agent-creator

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

FAQPage Schema

How do I generate a sub-agent configuration file from a text prompt?▼

You can generate a sub-agent configuration by providing a user description of the desired agent. The system outputs a ready-to-save Markdown file containing YAML frontmatter and a structured body detailing its purpose and instructions.

What is included in a Markdown sub-agent configuration file?▼

A Markdown sub-agent configuration includes YAML frontmatter with standardized fields like name, description, tools, model, and color, followed by a descriptive body detailing the agent's purpose and workflow instructions.

How do I define tools and models for AI automation agents?▼

You define tools and models through a guided requirements gathering workflow. By providing your agent's purpose and constraints, the system automatically maps them to a standardized frontmatter schema for your configuration.

Can I use this guided workflow to prototype sub-agents for product team automation?▼

Yes, product teams can use this workflow to rapidly prototype sub-agents for automation pipelines. For example, you can quickly generate a data-cleaner agent definition to handle data wrangling tasks without manual drafting.

What is the best way to ensure consistent agent definitions across a project?▼

The best way to ensure consistent agent definitions is automating creation with a standardized frontmatter schema. This prevents manual drafting errors and outputs structured Markdown files for every sub-agent.

Where are the generated sub-agent Markdown files saved?▼

The generated sub-agent configuration files are saved as Markdown files in the ai/shared/agents/ directory. The system outputs a ready-to-save file named after your specified agent.