Prompt Engineering For Agentic Systems |
Written by Nikos Vaggalis | |||
Thursday, 07 August 2025 | |||
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.
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
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:
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:
All in all this proved a very helpful repository in understanding why prompting is a quintessential part of the process
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