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AnanyaDBJ
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modify-agent

Customize an AI agent's Python code, system prompt, tools, and memory management.

6|10|Updated Mar 23, 2026
Search Tags:#customization#ai-agent#tool-integration#memory-management#system-prompt
One-click install
npx skills add https://github.com/AnanyaDBJ/databricks-ai-workshops --skill modify-agent-ananyadbj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: modify-agent
Source: https://github.com/AnanyaDBJ/databricks-ai-workshops/tree/main/advanced/.claude/skills/modify-agent
Command: npx skills add https://github.com/AnanyaDBJ/databricks-ai-workshops --skill modify-agent-ananyadbj

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Customize your AI agent's features, tools, language models, and prompts, enabling it to align with specific use cases and user expectations.

Core Features & Use Cases

  • Behavioral Customization: Modify agent behavior through Python script editing.
  • System Prompt Adjustment: Change the agent's persona and capabilities.
  • Tool Integration: Extend the agent's functionality by adding custom tools.
  • Memory Management: Customize how the agent stores and retrieves information.
  • Evaluation Customization: Define test cases and scorers for comprehensive assessment.
  • Use Case: A tech support agent can be tailored to provide more accurate and relevant information by adjusting the system prompt and integrating tools like documentation access.

Quick Start

Edit the agent_server/agent.py file to modify the LLM endpoint and SYSTEM_PROMPT, then add custom tools in the add-tools skill.

Frequently Asked Questions about modify-agent

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

FAQPage Schema
How do I customize an AI agent's system prompt and Python code?▼

Customize an AI agent by editing the `agent_server/agent.py` file to modify the LLM endpoint and `SYSTEM_PROMPT`, aligning the agent's persona and capabilities with specific use cases.

What is the best way to add custom tools to an AI agent?▼

The best way to add custom tools to an AI agent is by extending functionality through the `add-tools` skill, allowing the agent to access external documentation or perform specific integrated actions.

How does memory management work for customized AI agents?▼

Memory management for customized AI agents involves modifying how the agent stores and retrieves information, allowing advanced users to tailor data retention and context recall for varied scenarios.

Can I define custom test cases and evaluation methods for my AI agent?▼

Yes, you can define test cases and scorers for comprehensive assessment, enabling evaluation customization to measure the tailored agent's specific functionality and accuracy in varied scenarios.

Do I need advanced Python knowledge to modify my AI agent's behavior?▼

Yes, modifying the agent's behavior through Python script editing is tailored for advanced users seeking specific agent functionality, requiring familiarity with Python code and LLM endpoints.

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