> ## Documentation Index
> Fetch the complete documentation index at: https://docs.skillbridgedev.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Using AI Agents

> Learn how to interact with and use SkillShop's AI agents effectively

# Using AI Agents

SkillShop's AI agents are designed to be intuitive and conversational. This guide will help you understand how to interact with agents effectively and get the most out of their capabilities.

## Accessing Agents

### Navigation

1. **Main Navigation**: Click on "Agents" in the SkillShop sidebar
2. **Agent List**: Browse available agents in grid or list view
3. **Agent Details**: Click on any agent to view its details and start a conversation

### Agent Interface

The agent interface provides several key areas:

<Tabs>
  <Tab title="Overview">
    * Agent description and capabilities
    * Model configuration and settings
    * Usage statistics and performance metrics
  </Tab>

  <Tab title="Chat">
    * Interactive conversation interface
    * Real-time streaming responses
    * Tool usage visibility and progress tracking
  </Tab>

  <Tab title="Tools">
    * List of available tools for the agent
    * Tool descriptions and capabilities
    * Test individual tools with sample inputs
  </Tab>

  <Tab title="Prompt">
    * View the agent's system prompt (read-only for system agents)
    * Understand the agent's personality and expertise
    * Edit prompts for custom agents you've created
  </Tab>
</Tabs>

## Starting a Conversation

### Basic Interaction

Simply type your question or request in the chat interface. Agents understand natural language and can handle complex, multi-part requests.

<CodeGroup>
  ```text Example: Simple Question theme={null}
  "What are the key concepts in machine learning that I should include in a beginner's curriculum?"
  ```

  ```text Example: Complex Request theme={null}
  "Create a 4-week learning plan for high school students learning Python programming. Include assessments for each week and suggest hands-on projects."
  ```

  ```text Example: Follow-up theme={null}
  "Can you modify that plan to focus more on data analysis with Python instead of general programming?"
  ```
</CodeGroup>

### Best Practices for Agent Interaction

<AccordionGroup>
  <Accordion title="Be Specific and Clear">
    Provide clear context and specific requirements:

    * **Good**: "Create a quiz on photosynthesis for 8th grade students with 10 multiple choice questions"
    * **Better**: "Create a quiz on photosynthesis for 8th grade students with 10 multiple choice questions, focusing on the light-dependent reactions, and include explanations for each answer"

    <Note>
      Your specific request becomes the `{{ message }}` variable that agents use to personalize their responses.
    </Note>
  </Accordion>

  <Accordion title="Provide Context">
    Help agents understand your situation:

    * Grade level or audience
    * Subject area and specific topics
    * Learning objectives or goals
    * Time constraints or requirements
  </Accordion>

  <Accordion title="Ask Follow-up Questions">
    Agents maintain conversation context, so you can:

    * Request modifications to previous responses
    * Ask for clarification or additional details
    * Build on previous work iteratively
  </Accordion>

  <Accordion title="Leverage Agent Expertise">
    Each agent has specialized knowledge:

    * Ask curriculum agents about learning progressions
    * Request assessment agents to create rubrics
    * Have content agents generate multimedia materials
  </Accordion>
</AccordionGroup>

## Understanding Agent Responses

### Response Components

Agent responses typically include:

1. **Main Content**: The primary answer or deliverable
2. **Tool Usage**: Visible actions the agent took (searches, data lookups, etc.)
3. **Reasoning**: Explanation of the agent's approach
4. **Suggestions**: Recommendations for next steps or improvements

### Tool Usage Visibility

When agents use tools, you'll see:

* **Tool Name**: Which capability the agent is using
* **Purpose**: Why the agent chose this tool
* **Progress**: Real-time updates during tool execution
* **Results**: Summary of what the tool accomplished

<Note>
  Tool usage is transparent, so you can understand exactly how agents are gathering information and performing tasks.
</Note>

## Working with Different Agent Types

### System Agents

<Tabs>
  <Tab title="SkillShop Assistant">
    **Best for**: General questions, navigation help, platform guidance

    **Example requests**:

    * "How do I create a new learning path?"
    * "What's the difference between skills and topics?"
    * "Show me recent assessments in mathematics"
  </Tab>

  <Tab title="Curriculum Designer">
    **Best for**: Learning paths, course structure, educational progressions

    **Example requests**:

    * "Design a semester-long biology curriculum for high school"
    * "Create learning modules for teaching fractions to 4th graders"
    * "Suggest prerequisite skills for advanced calculus"
  </Tab>

  <Tab title="Assessment Designer">
    **Best for**: Quizzes, tests, rubrics, evaluation instruments

    **Example requests**:

    * "Create a formative assessment for the water cycle"
    * "Design a rubric for evaluating student essays"
    * "Generate practice problems for algebraic equations"
  </Tab>

  <Tab title="Content Creator">
    **Best for**: Educational materials, explanations, multimedia content

    **Example requests**:

    * "Write an engaging introduction to the Renaissance period"
    * "Create a step-by-step guide for solving quadratic equations"
    * "Generate discussion questions about climate change"
  </Tab>

  <Tab title="Learning Tutor">
    **Best for**: Student support, personalized explanations, learning guidance

    **Example requests**:

    * "Explain photosynthesis in simple terms for a struggling student"
    * "Provide study strategies for memorizing historical dates"
    * "Help a student understand why their math solution is incorrect"
  </Tab>
</Tabs>

### Workflow Agents

Workflow agents orchestrate complex processes involving multiple steps or agents:

<Steps>
  <Step title="Sequential Workflows">
    Execute agents one after another, passing results between them.

    **Example**: "Research → Design → Assess" content creation pipeline
  </Step>

  <Step title="Scheduled Workflows">
    Automate recurring educational tasks at specific times.

    **Example**: Weekly curriculum review and updates
  </Step>

  <Step title="Loop Workflows">
    Iterate on content until quality standards are met.

    **Example**: Refine assessment questions through multiple review cycles
  </Step>

  <Step title="Router Workflows">
    Intelligently delegate tasks to appropriate specialist agents.

    **Example**: Route different types of content requests to specialized creators
  </Step>
</Steps>

## Advanced Features

### Session Management

* **Conversation History**: Agents remember previous interactions within a session
* **Context Preservation**: Build on previous work without repeating information
* **Session Continuity**: Return to conversations later and continue where you left off

### Multi-Agent Collaboration

* **Agent Dispatch**: Agents can call other agents for specialized tasks
* **Workflow Integration**: Combine multiple agents for complex projects
* **Result Synthesis**: Agents can integrate outputs from multiple sources

### Customization Options

* **Model Selection**: Choose different AI models for different tasks
* **Temperature Settings**: Adjust creativity vs. consistency
* **Tool Configuration**: Enable or disable specific capabilities
* **Memory Settings**: Control how much context agents retain

## Troubleshooting Common Issues

<AccordionGroup>
  <Accordion title="Agent Not Responding">
    **Possible causes**:

    * Network connectivity issues
    * Agent model temporarily unavailable
    * Request too complex or ambiguous
    * Template variable processing errors

    **Solutions**:

    * Refresh the page and try again
    * Simplify your request
    * Try a different agent or rephrase your question
    * Check if agent has template variable issues (contact admin)
  </Accordion>

  <Accordion title="Unexpected Responses">
    **Possible causes**:

    * Insufficient context provided
    * Agent misunderstood the request
    * Tool limitations or data availability
    * Template variables not properly configured

    **Solutions**:

    * Provide more specific context and requirements
    * Ask clarifying questions
    * Try rephrasing your request
    * Ensure your message is clear and specific (it becomes the `{{ message }}` variable)
  </Accordion>

  <Accordion title="Tool Errors">
    **Possible causes**:

    * External service temporarily unavailable
    * Permission or authentication issues
    * Invalid parameters or data

    **Solutions**:

    * Check system status and try again later
    * Verify your permissions and access rights
    * Contact support if issues persist
  </Accordion>

  <Accordion title="Agent Execution Errors">
    **Possible causes**:

    * Agent template processing failed
    * Missing required template variables
    * Invalid system prompt configuration

    **Solutions**:

    * Try rephrasing your request with more context
    * Use a different agent if available
    * Report the issue to system administrators
    * Check agent configuration if you're the creator
  </Accordion>
</AccordionGroup>

## Tips for Success

<CardGroup cols={2}>
  <Card title="Start Simple" icon="play">
    Begin with straightforward requests to understand how each agent works, then gradually increase complexity.
  </Card>

  <Card title="Iterate and Refine" icon="refresh">
    Use follow-up questions to refine and improve agent responses rather than starting over.
  </Card>

  <Card title="Leverage Expertise" icon="brain">
    Match your requests to agent specializations for the best results and most relevant responses.
  </Card>

  <Card title="Provide Context" icon="info">
    The more context you provide, the better agents can tailor their responses to your specific needs.
  </Card>
</CardGroup>

## Next Steps

<Steps>
  <Step title="Try Different Agents">
    Experiment with various system agents to understand their unique capabilities and specializations.
  </Step>

  <Step title="Explore Agent Tools">
    Learn about the tools agents use to understand what they can accomplish for you.
  </Step>

  <Step title="Create Custom Agents">
    Once comfortable with system agents, consider creating custom agents for your specific needs.
  </Step>

  <Step title="Build Workflows">
    Explore workflow agents for complex, multi-step educational processes.
  </Step>
</Steps>