Troubleshooting

This guide covers common issues you may encounter when using AI Agents and how to resolve them.

General Troubleshooting Tips

When encountering issues with AI Agents, follow these steps:

1. Use the Agent Tester - The built-in tester in Lime Admin lets you run agents with different test objects and see exactly what's happening.
2. Start Simple - If an agent isn't working, simplify it. Remove Additional Input Data queries, reduce number of Output parameters, and simplify instructions. Add complexity back gradually once the basic version works.
3. Verify Your Data - Make sure your input object exists and has the expected properties. Check that Additional Input Data queries are returning the data you expect.
4. Review Instructions - Agent instructions should be clear, specific, and unambiguous. Vague instructions lead to unpredictable results.
5. Check the Logs - Logs for all AI requests are available in Lime Admin, under "System" → "AI" → "Logs".

Common Issues

Cannot Select "Run AI Agent" in Automation Step

Description

When building an automation in Lime Admin, the "Agent" action type does not appear in the available actions list, or it cannot be selected.

Solution

This happens when the "Run in background" switch has not been enabled for the automation.

Agent Performance is Slow

Description

Agent execution takes longer than expected, causing delays in automations or user actions.

Solution

Slow agent performance is typically caused by excessive data being sent in Additional Input Data queries.

Common causes:

• Queries returning hundreds or thousands of records
• Including large text fields (long descriptions, full email threads)
• Multiple queries each returning substantial data
• No limit set on query results

How to fix:

1. Always set a limit on Additional Input Data queries

   • Review each query and add a reasonable limit
   • Ask yourself: "Does the agent really need all these records?"

2. Filter query results

   • Use query filters to return only relevant records
   • Example: Instead of "all deals", query "open deals in last 90 days"

3. Select only necessary properties

   • Only include properties the agent needs for Input Object and Additional Input Data queries
   • Exclude large text fields unless essential

Important: More data doesn't always mean better results. Excessive irrelevant data often makes agent responses worse while also making execution slower and more expensive.

Agent Returns Unexpected Results

Description

The agent completes successfully but returns results that don't match expectations or seem incorrect.

Solution

1. Review agent instructions

   • Are they specific and unambiguous?
   • Do they include necessary domain knowledge?
   • Are there conflicting instructions?

2. Check input data

   • Use the agent tester with different test objects
   • Verify the input object has the expected properties
   • Confirm Additional Input Data queries are returning relevant data

3. Adjust instructions

   • Be more specific about what you want
   • Provide examples in the instructions
   • Break complex analysis into multiple fields

4. Try different models

   • Test with the "Powerful" model if using "Fast"
   • More complex reasoning tasks may need the more capable model