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Creating Custom Agents

While SkillShop’s system agents cover many common educational tasks, you can create custom agents tailored to your specific needs, teaching style, or unique educational contexts. Custom agents allow you to define specialized expertise, behavior, and tool access.
Custom agents use the same powerful infrastructure as system agents but can be personalized for your specific educational requirements and workflows.

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When to Create Custom Agents

Consider creating custom agents when you need:

Specialized Expertise

Subject-specific knowledge not covered by system agents (e.g., specialized medical training, niche technical skills)

Unique Teaching Style

Agents that match your specific pedagogical approach or institutional requirements

Custom Workflows

Agents designed for your organization’s specific processes and procedures

Targeted Audiences

Agents optimized for specific student populations, age groups, or learning contexts

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Agent Creation Process

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Step 1: Access Agent Creation

1

Navigate to Agents

Go to the Agents section in SkillShop’s main navigation
2

Click Create Agent

Use the “Create Agent” button in the top-right corner of the agents page
3

Choose Agent Type

Select “Custom Agent” to create a new agent from scratch

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Step 2: Basic Configuration

Agent Name: Unique identifier (no spaces, lowercase with underscores)
Example: "chemistry_lab_assistant"
Display Name: Human-readable name shown in the interface
Example: "Chemistry Lab Assistant"
Description: Clear explanation of the agent’s purpose and capabilities
Example: "Specialized assistant for high school chemistry lab activities, safety protocols, and experiment guidance"

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Step 3: System Prompt Design

The system prompt is the most important part of your agent - it defines the agent’s personality, expertise, and behavior patterns. SkillShop uses advanced template processing that allows you to create dynamic, context-aware prompts.

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Template Variables

Your system prompts can include template variables that are automatically filled in during conversations:
These variables are automatically available in all agent prompts:
{{ message }}     - The user's current message or request
{{ agentName }}   - Your agent's unique identifier  
{{ userId }}      - The current user's ID
{{ sessionId }}   - The conversation session ID
Example usage:
You are helping with this request: {{ message }}

As {{ agentName }}, your role is to provide specialized assistance.

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Prompt Structure

Define who the agent is and what they do:
You are a Chemistry Lab Assistant specialized in high school chemistry education. 
Your primary role is to help students and teachers with laboratory activities, 
safety protocols, and experimental procedures.
Specify the agent’s areas of expertise:
Your expertise includes:
- Laboratory safety protocols and procedures
- Common high school chemistry experiments
- Equipment usage and maintenance
- Chemical properties and reactions
- Troubleshooting experimental problems
- Data analysis and interpretation
Define how the agent should interact:
Your communication style should be:
- Clear and safety-focused
- Patient and encouraging with students
- Detailed when explaining procedures
- Always emphasizing safety first
- Supportive of student curiosity and learning
Set important limitations and guidelines:
Important guidelines:
- Always prioritize safety in all recommendations
- Encourage proper lab procedures and protocols
- When unsure about safety, recommend consulting a teacher
- Provide step-by-step instructions for complex procedures
- Use age-appropriate language for high school students

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Example Complete Prompt with Template Variables

You are a Chemistry Lab Assistant specialized in high school chemistry education. 
Your primary role is to help students and teachers with laboratory activities, 
safety protocols, and experimental procedures.

Current Request: {{ message }}
Student Level: {{ gradeLevel? }}
Safety Context: {{ safetyLevel? }}

Your expertise includes:
- Laboratory safety protocols and procedures
- Common high school chemistry experiments (acid-base reactions, 
  stoichiometry labs, gas laws, etc.)
- Equipment usage and maintenance
- Chemical properties and reactions
- Troubleshooting experimental problems
- Data analysis and interpretation

Your communication style should be:
- Clear and safety-focused
- Patient and encouraging with students
- Detailed when explaining procedures
- Always emphasizing safety first
- Supportive of student curiosity and learning

Important guidelines:
- Always prioritize safety in all recommendations
- Encourage proper lab procedures and protocols
- When unsure about safety, recommend consulting a teacher
- Provide step-by-step instructions for complex procedures
- Use age-appropriate language for high school students
- Reference relevant safety data sheets when appropriate

When helping with experiments, always include:
1. Safety considerations and required PPE
2. Step-by-step procedures tailored to: {{ message }}
3. Expected observations and results
4. Common troubleshooting tips
5. Connections to underlying chemical principles

{{ docs/chemistry/safety-protocols.md }}
The template variables ({{ message }}, {{ gradeLevel? }}, etc.) are automatically filled in when users interact with your agent, making responses more personalized and contextual.

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Step 4: Model Configuration

Choose the AI model that powers your agent:Claude 3.5 Haiku: Fast, efficient, good for simple tasks Claude 3.5 Sonnet: Balanced performance and capability Claude 3 Opus: Most capable, best for complex reasoning GPT-4: Alternative high-performance option
Start with Claude 3.5 Sonnet for most educational tasks - it provides excellent performance with reasonable speed.

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Step 5: Tool Selection

Choose which tools your agent can access:
Data Lookup: Access SkillShop’s database of topics, skills, and content Content Search: Search educational materials and resources Text Processing: Analyze and transform text content
These tools are recommended for most educational agents.
Assessment Manager: Create and manage assessments (for assessment-focused agents) Learning Plan Manager: Create learning plans and modules (for curriculum agents) Content Discovery: Find external educational content (for content agents) Calculator: Mathematical operations (for STEM agents) Google Sheets: Spreadsheet operations (for data-focused agents)
Code Generator: Generate and analyze code (for programming agents) Issue Manager: Manage development issues (for technical agents) Agent Dispatch: Call other agents (for orchestration agents)

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Step 6: Testing and Refinement

1

Initial Testing

Test your agent with sample questions and requests to verify it behaves as expected
2

Prompt Refinement

Adjust the system prompt based on testing results - add constraints, clarify behavior, or expand expertise
3

Tool Validation

Verify the agent can effectively use its assigned tools for intended tasks
4

User Testing

Have colleagues or students test the agent and provide feedback

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Advanced Agent Features

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Tool Choice Configuration

Control how your agent uses tools:

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Context and Memory Management

Configure how your agent handles conversation context:
  • Session Continuity: Maintain context within conversation sessions
  • Cross-Session Memory: Remember information across different conversations
  • Context Limits: Set maximum context length to manage performance
  • Memory Cleanup: Automatically clear sensitive information

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Example Custom Agents

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STEM Lab Assistant

Agent Name: stem_lab_assistant
Display Name: STEM Lab Assistant
Category: Tutoring

System Prompt:
You are a STEM Lab Assistant specializing in hands-on science, technology, 
engineering, and mathematics activities for middle and high school students.

Your expertise includes:
- Laboratory safety and procedures across all STEM disciplines
- Equipment usage (microscopes, sensors, programming tools, etc.)
- Experimental design and data collection
- Mathematical modeling and analysis
- Engineering design process
- Technology integration in STEM learning

Always prioritize safety, encourage scientific thinking, and help students 
connect hands-on activities to underlying STEM principles.

Tools: data_lookup, content_search, calculator, text_processing

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Special Education Support Agent

Agent Name: special_education_assistant
Display Name: Special Education Assistant
Category: Tutoring

System Prompt:
You are a Special Education Assistant focused on supporting students with 
diverse learning needs and abilities.

Your expertise includes:
- Differentiated instruction strategies
- Accommodations and modifications
- Multi-sensory learning approaches
- Behavioral support strategies
- Assistive technology integration
- IEP goal alignment

Adapt your communication style to individual student needs, provide multiple 
ways to access content, and always maintain a patient, encouraging approach.

Tools: data_lookup, content_search, text_processing, learning_plan_manager

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Language Arts Writing Coach

Agent Name: writing_coach
Display Name: Writing Coach
Category: Tutoring

System Prompt:
You are a Writing Coach specializing in helping students develop their 
writing skills across various genres and purposes.

Your expertise includes:
- Writing process guidance (planning, drafting, revising, editing)
- Genre-specific writing strategies
- Grammar and mechanics instruction
- Peer review and feedback techniques
- Digital writing tools and platforms
- Portfolio development

Provide constructive, specific feedback that helps students grow as writers 
while maintaining their unique voice and creativity.

Tools: data_lookup, content_search, text_processing, assessment_manager

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Best Practices

Clear Purpose

Define a specific, focused purpose for your agent rather than trying to make it do everything

Consistent Personality

Maintain a consistent voice and approach throughout the system prompt

Safety First

Always include appropriate safety guidelines and constraints for your domain

Iterative Improvement

Continuously test and refine your agent based on real usage and feedback

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Managing Custom Agents

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Editing Agents

  • Prompt Updates: Modify system prompts to improve behavior
  • Tool Changes: Add or remove tools based on usage patterns
  • Model Upgrades: Switch to newer or more appropriate models
  • Configuration Tuning: Adjust temperature and token limits

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Sharing Agents

  • Public Sharing: Make agents available to your organization
  • Export/Import: Share agent configurations with other SkillShop instances
  • Version Control: Track changes and maintain agent versions
  • Collaboration: Allow team members to contribute to agent development

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Performance Monitoring

  • Usage Analytics: Track how often and how effectively your agent is used
  • Response Quality: Monitor user satisfaction and feedback
  • Tool Usage: Analyze which tools are most valuable for your agent
  • Cost Management: Monitor token usage and computational costs

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Troubleshooting Common Issues

Solution: Add more specific expertise and constraints to your system prompt. Include domain-specific knowledge and examples. Use template variables like {{ message }} to make responses more contextual.
Solution: Explicitly mention tool usage in the system prompt and provide examples of when to use specific tools.
Solution: Lower the temperature setting and add more specific behavioral guidelines to the system prompt.
Solution: Adjust max tokens setting and include response length guidelines in the system prompt.
Possible causes:
  • Using undefined variables in your prompt
  • Incorrect variable syntax
  • Missing required variables
Solutions:
  • Use built-in variables: {{ message }}, {{ agentName }}, {{ userId }}, {{ sessionId }}
  • Check syntax: {{ variable }} (required), {{ variable? }} (optional)
  • Test your agent to ensure all variables are properly resolved
Possible causes:
  • Required template variables are missing
  • Invalid template syntax in system prompt
  • Referenced documents or prompts don’t exist
Solutions:
  • Review system prompt for template variable errors
  • Ensure referenced documents exist: {{ docs/path/file.md }}
  • Use optional syntax {{ variable? }} for non-critical variables

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Next Steps

1

Plan Your Agent

Identify a specific educational need not met by existing system agents
2

Create and Test

Build your agent using the creation interface and test thoroughly
3

Gather Feedback

Share with colleagues and students to gather improvement suggestions
4

Iterate and Improve

Continuously refine based on usage patterns and feedback
5

Explore Workflows

Consider creating workflow agents that combine your custom agent with others