Can I use this for multi-agent systems?

Yes, the skill includes specific templates and guidance for subagent orchestration and delegating complex tasks to specialized agents within a larger workflow.

Does it help with model verbosity?

Absolutely. It includes strategies to control output formatting, reduce unnecessary markdown, and adjust how proactive an agent is when interacting with the user.

Is this skill specific to Claude?

While it is optimized for Claude Code and the Claude model family, the core principles of agentic prompting apply to most modern large language models used in autonomous workflows.

How does this skill improve agent behavior?

It provides explicit patterns for framing instructions, adding context, and using structural elements like XML tags to ensure models understand their specific goals and behavioral constraints.

Agentic Prompt Crafting

Name: Agentic Prompt Crafting
Author: Mission42-ai

byMission42-ai

Data Science & ML

Optimizes AI agent behavior through specialized prompt engineering patterns and best practices for complex, autonomous workflows.

About

This skill provides comprehensive guidance and proven templates for designing high-performance system prompts for autonomous agents. It helps developers fine-tune agentic behavior—such as proactivity levels, tool-calling efficiency, and verbosity control—to ensure more reliable results in long-horizon reasoning and specialized tasks like research, document creation, or frontend generation. By utilizing XML-structured templates and explicit instruction principles, users can significantly reduce hallucinations and improve the success rate of complex subagent orchestrations.

Key Features

0 GitHub stars
Proven system prompt templates for diverse agentic personas and tasks
Optimization patterns for parallel tool calling and subagent orchestration
Strategies for controlling output verbosity and formatting via XML tags
Reasoning frameworks for long-horizon tasks and state management
Best practices for hallucination reduction and improved accuracy

Use Cases

Setting up multi-step workflows where a primary agent delegates to specialized subagents
Crafting coding assistants that adhere to strict UI/UX design and styling requirements
Building proactive research agents that autonomously synthesize data and cite sources

About

Key Features

0 GitHub stars
Proven system prompt templates for diverse agentic personas and tasks
Optimization patterns for parallel tool calling and subagent orchestration
Strategies for controlling output verbosity and formatting via XML tags
Reasoning frameworks for long-horizon tasks and state management
Best practices for hallucination reduction and improved accuracy

Use Cases

Setting up multi-step workflows where a primary agent delegates to specialized subagents
Crafting coding assistants that adhere to strict UI/UX design and styling requirements
Building proactive research agents that autonomously synthesize data and cite sources