Prompt Engineering For Agentic Systems

Introducing a Github repository that delves into ways of constructing prompts that squeeze performance out when building AI Agents

It’s no secret that better prompts give better results, always.
As such, the “Crafting Effective Prompts for Agentic AI Systems: Patterns and Practices” Github repository is a treasure trove of information that shows how to use prompting efficiently by analyzing the system prompts that power on popular AI tools such as Vercel’s v0, Manus, OpenAI’s ChatGPT etc, to extract recurring patterns and best practices. These patterns then can be used in building your own agents to make them powerful, predictable, and trustworthy AI assistants.

The repository goes through the core principles of Agentic Prompts that were identified during that research, which we briefly enumerate:

1. Clear Role Definition and Scope

2. Structured Instructions and Organization

3. Explicit Tool Integration and Usage Guidelines

4. Step-by-Step Reasoning and Planning

5. Environment and Context Awareness

6. Domain-Specific Expertise and Constraints

7. Safety, Alignment, and Refusal Protocols

8. Consistent Tone and Interaction Style

Each concept is then analyzed and demonstrated with an example prompt. For instance under “Clear Role Definition and Scope”, we find that:

Explicitly defining the AI’s identity, core function, and operational domain anchors its behavior, sets user expectations, and helps prevent scope creep or nonsensical responses. It tells the AI who it is and what it’s supposed to do.

Example prompt: Manus: Introduces itself and lists broad task categories it excels at.

You are Manus, an AI agent created by the Manus team.

You excel at the following tasks:
1. Information gathering…
2. Data processing…
3. Writing multi-chapter articles…
…

After covering the principles, the repo continues with examining how they can manifest in specific agent prompts. It wraps everything up with the key takeaways builders should leave with, such as:

Define the Agent Clearly

Structure for Clarity

Be Explicit About Tools

All in all this proved a very helpful repository in understanding why prompting is a quintessential part of the process
of building your agents and how to go about it with practical examples. Recommended.

More Information

Awesome AI System prompts

Agentic AI For PostgreSQL

To be informed about new articles on I Programmer, sign up for our weekly newsletter, subscribe to the RSS feed and follow us on Twitter, Facebook or Linkedin.