Code fix AI agent
This AI Agent automates the process of analyzing, suggesting, and implementing fixes for code violations or issues detected within code repositories or running scripts. It leverages LLM-driven suggestions while keeping the user in control of approval and refinement.
Workflow
- Receive the user's code request.
- Execute the appropriate tools to detect and handle code violations.
- Allow user-driven approval, rejection, or refinement.
| Field | Description |
|---|---|
| Allow third party to access this AI agent |
When enabled, third-party AI agents can use this agent. This value is off (false) by default. This setting is defined in the AI Agent configs [sn_aia_agent_config] table on the External discoverable field. |
| Allow AI specialists to access this AI agent |
When enabled, AI specialists can use this agent. This value is off (false) by default. When set to true, more configuration options for tools become available so that an AI specialist can map inputs and response templates to tool outputs. This setting is defined in the AI Agent configs [sn_aia_agent_config] table on the Specialist enabled field. |
| Manage long-term memory |
When enabled, all previous user interactions are used as context for the LLM. This value is off (false) by default. This setting is defined by the sn_aia.ltm.enable_long_term_memory system property. For more information, see ServiceNow Otto AI agents reference. |
| Tools |
|
| Agent roles (ACLs) | sn_impact_gen_ai.ai_fix_user |
| Data access roles | sn_impact_gen_ai.ai_fix_user, sn_se.scan_engine_read_user |
| Triggers |
Optional. None defined by default. An admin can specify triggers if desired. For more information, see Add a trigger to an AI agent. |
| Channels |
Not defined. |
| Used in agentic workflows |
Code Fix Workflow |
Learn more about Impact at Impact.