Creating Agents

This guide walks you through creating a new AI agent from scratch, covering configuration options and best practices.

Prerequisites

Access to Agent Studio
Understanding of your use case and goals
Knowledge of what tools the agent will need

Step 1: Start a New Agent

Navigate to Agent Studio from the main navigation
Click Agents in the sidebar
Click Create Agent or the + button

You’ll see the agent configuration form.

Step 2: Basic Information

Agent Name

Choose a descriptive name that indicates the agent’s purpose:

Good Names	Poor Names
”Account Health Analyzer"	"Agent 1"
"QBR Prep Assistant"	"Helper"
"Renewal Risk Monitor"	"AI Bot”

Names should help users quickly understand what the agent does without reading the full description.

Step 3: Write Instructions

Instructions (the system prompt) define how your agent behaves. This is the most important configuration.

Structure Your Instructions

# Role
[Who the agent is and what it specializes in]

# Primary Tasks
[What the agent should do when asked]

# Guidelines
[How the agent should approach tasks]

# Output Format
[How responses should be structured]

# Constraints
[What the agent should avoid]

Example: Customer Health Agent

# Role
You are a customer success analyst specializing in account health assessment and early warning detection.

# Primary Tasks
When analyzing an account:
1. Review health score trends over the past 90 days
2. Analyze engagement patterns from activities
3. Identify key contacts and their recent involvement
4. Compare against similar successful accounts
5. Generate specific, actionable recommendations

# Guidelines
- Base all conclusions on data, not assumptions
- Prioritize actionable insights over general observations
- Consider both quantitative metrics and qualitative signals
- Explain your reasoning clearly

# Output Format
Structure your analysis as:

## Health Assessment
[Overall assessment with health score context]

## Key Findings
- [Finding 1 with data support]
- [Finding 2 with data support]

## Risk Factors
- [Risk 1]: [Mitigation suggestion]

## Recommended Actions
1. [Specific action with expected outcome]
2. [Specific action with expected outcome]

# Constraints
- Never fabricate data or statistics
- Don't make promises about outcomes
- If data is insufficient, say so explicitly

Step 4: Select the Model

Choose the AI model based on your needs:

Model Options

Model	Speed	Capability	Cost	Best For
Gemini Auto	Varies	Varies	Optimized	Most use cases
Gemini 3 Pro	Slower	Highest	Higher	Complex analysis, critical tasks
Gemini 3 Flash	Fastest	Good	Lower	Quick queries, simple tasks
Gemini 2.5 Flash	Fast	Very Good	Moderate	Balanced needs

Recommendations

Start with Gemini Auto - Let the system optimize model selection
Use Pro for complex research, multi-step analysis, or critical decisions
Use Flash for quick lookups, simple formatting, or high-volume tasks

Step 5: Configure Reasoning Level

Reasoning level controls how much the agent “thinks” before responding:

Options

Level	Behavior	Use When
Auto	Adapts to task complexity	You’re unsure what level is needed
Low	Quick, direct responses	Simple questions, factual lookups
Medium	Moderate analysis	Standard analysis, most tasks
High	Deep reasoning	Complex problems, nuanced analysis

Higher reasoning = better analysis but slower responses and higher cost. Match the level to your actual needs.

Step 6: Enable Toolkits

Toolkits give your agent capabilities. Enable only what’s needed.

Available Toolkits

Toolkit	Capabilities	Enable When
Account Data	Get account details, health scores, custom fields	Agent needs account information
Activity Data	Fetch activities, emails, meetings	Agent analyzes engagement
Contact Data	Get contact details, roles, engagement	Agent works with people
Task Management	Create/update tasks, add comments	Agent manages follow-ups
Project Data	Get project status, tasks, timelines	Agent reviews implementations
Communication	Send emails, Slack messages	Agent takes outreach actions
CRM Integration	Salesforce/HubSpot operations	Agent syncs with CRM
Knowledge Base	Search documents, articles	Agent needs reference materials
Data Analysis	Run Python code for accurate counting, aggregation, and data calculations	Agent needs precise arithmetic or data analysis

Guidelines

Less is more

Each enabled toolkit adds complexity. An agent with 3 focused toolkits will often outperform one with 10 toolkits.

Match to purpose

A health analysis agent needs Account + Activity data. It probably doesn’t need Task Management or Communication.

Consider the user

Will users expect the agent to take actions (create tasks, send messages) or just provide information?

Step 7: Set Scope

Define what data the agent can access:

Scope Options

Scope	Access	Use For
Global	All organization data	General-purpose agents
Account	Specific account context	Account-focused workflows

Account Scope

When using account scope:

Agent can only access data for the specified account
Useful for embedding agents in account-specific contexts
Provides data isolation and relevance

Step 8: Add Datasets (Optional)

Connect specific data sources for the agent to reference:

Knowledge bases - Internal documentation
Playbooks - Standard procedures
Templates - Response templates

This gives the agent access to your organization’s specific knowledge.

Step 9: Add a Presentation Template (Optional)

If your agent generates presentations, you can give it its own branded PowerPoint template:

In the Presentation Template section, click Upload Template
Select a .pptx file (PowerPoint format)
Once uploaded, the section shows Template uploaded with Replace and Remove buttons

Template Mode

After uploading, choose how the agent uses your template:

Mode	Behavior	Use When
Brand Guide (Creative)	AI creates new slides inspired by your template’s look & feel	You want on-brand decks with flexible layouts (default)
Strict Template	AI fills content into your template’s existing slide structure	Your deck must follow a fixed slide-by-slide format

An agent’s own template takes priority over your organization’s default presentation template. To set the organization-wide default instead, see Stella AI advanced features.

Step 10: Test Your Agent

Before deploying, test thoroughly.

Test Scenarios

Typical request
- Ask something your users commonly would
- Verify the response is helpful and accurate
Ambiguous request
- Ask something vague
- Does the agent ask clarifying questions or make reasonable assumptions?
Edge case
- Ask about an account with missing data
- How does the agent handle incomplete information?
Out of scope
- Ask something outside the agent’s purpose
- Does it gracefully redirect or explain limitations?

Example Test Prompts

Test 1: "Tell me about Acme Corp's health"
Expected: Detailed analysis with specific metrics

Test 2: "Acme Corp"
Expected: Asks what information is needed OR provides summary

Test 3: "What's the weather?"
Expected: Explains it can't help with that / redirects to purpose

Step 11: Deploy

Once tested:

Click Save to save your agent
Toggle Active to enable it
The agent is now available for use

Configuration Examples

Research-Focused Agent

Name: Account Research Assistant
Model: Gemini 3 Pro
Reasoning: High
Toolkits: Account Data, Activity Data, Contact Data
Scope: Global

Instructions:
You conduct deep research on customer accounts. When asked about
an account, provide comprehensive analysis covering health metrics,
engagement trends, key contacts, and strategic recommendations.
Always cite specific data points and explain your reasoning.

Action-Oriented Agent

Name: Task Creator
Model: Gemini 2.5 Flash
Reasoning: Medium
Toolkits: Account Data, Task Management
Scope: Account

Instructions:
You help users quickly create and manage tasks. When asked to create
a task, gather the essential information (title, assignee, due date)
and create it immediately. Keep interactions concise and efficient.

Communication Agent

Name: Outreach Drafter
Model: Gemini Auto
Reasoning: Medium
Toolkits: Account Data, Activity Data, Contact Data
Scope: Account

Instructions:
You draft personalized outreach messages. When asked to draft an
email or message, research the account and contacts first, then
create tailored content that references specific context. Always
output in a ready-to-send format.

Best Practices Summary

Start simple

Begin with minimal toolkits and instructions. Add complexity only when needed.

Be specific in instructions

Vague instructions lead to inconsistent results. Be explicit about what you want.

Test with real data

Sample data doesn’t catch real-world issues. Test with actual accounts and scenarios.

Iterate based on feedback

Your first version won’t be perfect. Collect feedback and refine instructions.

Monitor performance

Track how the agent is being used and whether responses are helpful.

Next Steps

Agent Best Practices

Advanced tips for agent optimization

Use Agents in Automations

Embed agents in workflow automations

Getting Started

Automations

AI Agents

Creating Agents

Creating Agents

Prerequisites

Step 1: Start a New Agent

Step 2: Basic Information

Agent Name

Step 3: Write Instructions

Structure Your Instructions

Example: Customer Health Agent

Step 4: Select the Model

Model Options

Recommendations

Step 5: Configure Reasoning Level

Options

Step 6: Enable Toolkits

Available Toolkits

Guidelines

Step 7: Set Scope

Scope Options

Account Scope

Step 8: Add Datasets (Optional)

Step 9: Add a Presentation Template (Optional)

Template Mode

Step 10: Test Your Agent

Test Scenarios

Example Test Prompts

Step 11: Deploy

Configuration Examples

Research-Focused Agent

Action-Oriented Agent

Communication Agent

Best Practices Summary

Next Steps

Agent Best Practices

Use Agents in Automations

​Creating Agents

​Prerequisites

​Step 1: Start a New Agent

​Step 2: Basic Information

​Agent Name

​Step 3: Write Instructions

​Structure Your Instructions

​Example: Customer Health Agent

​Step 4: Select the Model

​Model Options

​Recommendations

​Step 5: Configure Reasoning Level

​Options

​Step 6: Enable Toolkits

​Available Toolkits

​Guidelines

​Step 7: Set Scope

​Scope Options

​Account Scope

​Step 8: Add Datasets (Optional)

​Step 9: Add a Presentation Template (Optional)

​Template Mode

​Step 10: Test Your Agent

​Test Scenarios

​Example Test Prompts

​Step 11: Deploy

​Configuration Examples

​Research-Focused Agent

​Action-Oriented Agent

​Communication Agent

​Best Practices Summary

​Next Steps

Agent Best Practices

Use Agents in Automations

Creating Agents

Prerequisites

Step 1: Start a New Agent

Step 2: Basic Information

Agent Name

Step 3: Write Instructions

Structure Your Instructions

Example: Customer Health Agent

Step 4: Select the Model

Model Options

Recommendations

Step 5: Configure Reasoning Level

Options

Step 6: Enable Toolkits

Available Toolkits

Guidelines

Step 7: Set Scope

Scope Options

Account Scope

Step 8: Add Datasets (Optional)

Step 9: Add a Presentation Template (Optional)

Template Mode

Step 10: Test Your Agent

Test Scenarios

Example Test Prompts

Step 11: Deploy

Configuration Examples

Research-Focused Agent

Action-Oriented Agent

Communication Agent

Best Practices Summary

Next Steps