Prompting for Agents | LIZIU AI Agents

System Prompts for Agents

Why Prompting Matters

The Problem: An LLM without proper instructions is like a brilliant employee with no job description -- capable but directionless.

The Solution: Well-crafted system prompts transform a general-purpose LLM into a focused, reliable agent with clear behavior, tool awareness, and error handling strategies.

Real Impact: The difference between a mediocre agent and an excellent one is often just the quality of its system prompt.

Real-World Analogy

Think of a system prompt as an employee onboarding packet:

Role Definition = Job title and responsibilities
Tool Documentation = List of software and tools they can use
Guidelines = Company policies and best practices
Examples = Sample work from previous employees
Constraints = What they should never do

Anatomy of an Agent Prompt

Identity & Role

Define who the agent is, its expertise, and personality. This anchors all subsequent behavior.

Capabilities

List what tools the agent can use, what actions it can take, and the scope of its abilities.

Instructions

Step-by-step guidance on how to approach tasks, handle errors, and format responses.

Constraints

Boundaries the agent must respect -- safety guardrails, scope limits, and fallback behaviors.

Role & Persona Definition

Prompt Structure Breakdown

Tool Descriptions in Prompts

agent_system_prompt.txt

# System Prompt for a Research Agent

You are a research assistant with expertise in technology topics.

## Your Tools
- web_search(query): Search the internet for current info.
- read_url(url): Read the full content of a web page.
- save_note(content): Save important findings for later.

## Instructions
1. Always search before answering factual questions.
2. Cite your sources with URLs.
3. If sources disagree, present both viewpoints.
4. Think step-by-step for complex questions.

## Constraints
- Never fabricate information or URLs.
- If you cannot find reliable info, say so clearly.
- Limit searches to 3 per question to manage costs.

Few-Shot Examples

few_shot_prompt.py

messages = [
    {"role": "system", "content": system_prompt},
    # Few-shot example: demonstrate tool usage
    {"role": "user", "content": "What is the latest Python version?"},
    {"role": "assistant", "content": "Let me search for the latest Python release.",
     "tool_calls": [{"function": {"name": "web_search",
      "arguments": "latest python version 2026"}}]},
    {"role": "tool", "content": "Python 3.14 released..."},
    {"role": "assistant", "content": "Python 3.14 was released. [Source: python.org]"},
    # Now the actual user query
    {"role": "user", "content": actual_query}
]

Prompt Templates

Template	When to Use	Example
Role-Goal-Constraints	General-purpose agents	"You are X. Your goal is Y. Never do Z."
Tool-First	Tool-heavy agents	Lead with tool definitions and usage rules
Chain-of-Thought	Reasoning-intensive	"Think step-by-step before acting"
Output-Format	Structured output	Specify exact JSON schema in prompt

Quick Reference

Principle	Do	Don't
Clarity	Be specific and explicit	Use vague instructions
Structure	Use headers and lists	Write a wall of text
Examples	Show desired behavior	Only describe abstractly
Constraints	State boundaries explicitly	Assume model will infer limits
Testing	Iterate and refine prompts	Write once and deploy