--- sourceDocument: Brazil Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/intelligent-experiences Release : - brazil ft:locale : - en-US ft:publication_title : - Brazil Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # Run results page # Agentic evaluation run results {#ariaid-title1} Release version: Brazil Updated September 10, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Agentic Evaluation Run Results Agentic evaluations in ServiceNow assess how effectively AI agents and agentic workflows achieve their objectives by analyzing execution logs using a Now LLM Service model. These evaluations provide multiple metrics on task completeness and tool usage, helping you understand the performance of your AI agents and workflows. Show full answer Show less The evaluation results page displays overall scores with labels indicating performance quality, and it offers recommended actions to guide deployment or improvement decisions. After reviewing, you can archive, duplicate, or export evaluation results as a CSV report containing individual execution record IDs and their metric scores. For broader insights, you can also use the AI Agent Analytics dashboard in AI Agent Studio. ## Evaluation Results Overview Each evaluation run provides an overall task completeness score expressed as a percentage of successfully completed records, accompanied by a performance label: * **Excellent (90%-100%)**: High standard task completion; suitable for confident deployment. * **Good (70%-89%)**: Mostly successful with some inconsistencies; deploy with caution. * **Moderate (50%-69%)**: Many incomplete tasks; requires investigation before deployment. * **Poor (0%-49%)**: Consistent failure in task completion; deployment is not recommended. You can customize the metric thresholds that determine these labels. ## Individual Record Metric Scores Each execution record is scored individually on the following key metrics, helping you pinpoint specific performance areas: * **Overall Task Completeness** : Measures if the AI agent fully completed its task logically and without critical errors. * 3 - Successful: Task and all subtasks fully completed. * 2 - Partially successful: Some subtasks unresolved or inefficiencies present. * 1 - Unsuccessful: Task not completed or critical failures occurred. * **Tool Performance** : Evaluates whether the AI agent selected the correct tool for each action. * 1 - True: Correct tool chosen. * 0 - False: Incorrect tool chosen. * **Tool Calling Records** : Assesses if tool calls were constructed correctly, validating input keys, values, and formatting. * 1 - True: All required parameters are present and correctly formatted. * 0 - False: Missing parameters, incorrect mappings, or wrong formats detected. *Note:* All sub-metrics for tool calling must be true for an overall true score; otherwise, the score is false. ## What This Enables for You By using agentic evaluation results, you gain actionable insights into your AI agents' performance, enabling informed decisions on deploying, refining, or troubleshooting your agentic workflows. The detailed metrics help you identify specific areas needing improvement, ensuring your AI workflows meet your operational standards and perform reliably in production. Learn about agentic evaluation runs and the meaning behind different evaluation scores from the agentic evaluation results page. ## Agentic evaluations overview Agentic evaluations measure how well AI agents and agentic workflows are accomplishing their objectives. A Now LLM Service model judges the AI agent or agentic workflow based on the execution logs. The results page of an evaluation run shows multiple metrics and scores measuring task completeness and tool use. If you run an overall task completion evaluation, the results page shows recommended actions for the AI agent or agentic workflow. Recommended actions give you suggestions for deployment or improvement to help verify that the agentic workflows that you deploy are performing up to your standards. After you've reviewed your evaluation results, you can archive your evaluation or copy it to run another evaluation with the same parameters and dataset. You can export the evaluation results as a report. The report is formatted as a .csv file that includes the individual sys_ids of the execution records and the metric scores for each. For more information on AI agent usage and other analytics, you can review the [AI Agent Analytics dashboard](https://www.servicenow.com/docs/yfDyVbCfrQIJR5XUzKrrFA "Track the AI agent use and efficiency gain on your instance through the AI Agent Analytics dashboard. The dashboard can reveal trends in how AI agents are used to improve the time to resolution and the number of tasks closed.") in the AI Agent Studio. ## Evaluation results overview For each evaluation method that you execute, the results page displays an overall score for the agentic workflow with a percentage of successful record evaluations and a label of Excellent, Good, Moderate, or Poor. You can change the metric thresholds for each label by selecting Customize metric thresholds. In addition to the overall task completeness results, you can review a summary of the results of the other metrics. {#aia-eval-metrics__entry__4} | Label | Description | Recommended action | Default threshold | |-|-|-|-| | Excellent | Tasks were consistently performed at a high standard. The agentic workflow or AI agent is working well. | Proceed with confidence | 90%--100% | | Good | Most tasks were performed successfully, but some performance inconsistencies suggest areas for improvement. | Deploy with caution | 70%--89% | | Moderate | A significant number of tasks weren't fully completed. Performance is below the desired level. | Investigate the root causes of poor task completion | 50%--69% | | Poor | The agentic workflow is consistently failing to complete tasks adequately. Major issues are present. | Do not deploy | 0%--49% | [Table 1. Overall task completeness evaluation run results] ## Individual record metric scores Evaluations are run against the log tables of agentic workflow executions. Each record is individually scored for each evaluation plan that you run. Individual record evaluations are scored according to the following metrics. {#aia-eval-metrics__entry__23} | Number | Score | Description | |-|-|-| | 3 | Successful | The main task was fully completed. All subtasks were resolved, and the steps followed a logical sequence with no critical errors. | | 2 | Partially successful | The task was partially completed. Some subtasks remain unresolved or inefficiencies affected the process. | | 1 | Unsuccessful | The task wasn't completed. Critical subtasks were abandoned or unresolved or the execution failed entirely. | [Table 2. Overall task completeness record metric scoresThe overall task completeness metric assesses whether an AI agent successfully completes its assigned task. It evaluates the execution logs of the agent, ensuring that all required steps were taken and the task was logically and effectively completed.] {#aia-eval-metrics__entry__35} | Number | Score | Description | |-|-|-| | 1 | True | The right tool was chosen for the action in the plan. | | 0 | False | The right tool wasn't chosen. | [Table 3. Tool performance record metric scoresThe tool performance evaluation metric assesses an AI agent's ability to select the most appropriate tool for each step while completing a task.] {#aia-eval-metrics__entry__44} | Number | Score | Description | |-|-|-| | 1 | True | Input key completeness, input value correctness, and input format correctness are all successful. * Input key completeness: 1 - True -- All required parameters are present with exact name matches, and no unexpected parameters are included. * Input value correctness: 1 - True -- Tool input values are correctly mapped. * Input format correctness: 1 - True -- Tool inputs are in the correct format. | | 0 | False | One or more of input key completeness, input value completeness, or input format completeness wasn't successful. * Input key completeness: 0 - False -- A mandatory parameter is either missing, its name doesn't match exactly, or an unexpected parameter was found. * Input value correctness: 0 - False -- Tool input values are not correctly mapped. * Input format correctness: 0 - False -- Tool inputs are not in the correct format. | [Table 4. Tool calling records metric scoresThe tool calling evaluation metric assesses whether an AI agent correctly constructs tool calls by validating the accuracy, completeness, and formatting of the inputs it provides.] Note: The values of the sub-metrics are aggregated using an AND operator. If any one value is 0, then the entire tool calling records metric score will be 0.