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This page describes how to configure general Mainframe Assessment Tool settings
and modify default AI features for new assessments.
The modified settings don't apply to existing assessments. To use modified
settings, create a new assessment.
Configure general settings
To configure general settings for your assessment, follow these steps:
Click the settingsSettings icon.
To edit your preferences for Cloud Logging and Google Analytics,
in the General settings section, do the following:
To enable Logging, click Enable Cloud Logging.
By default, Cloud Logging is disabled. Using Cloud Logging might incur
additional costs. For more information, see Cloud Logging
documentation.
To enable Google Analytics, click Enable Google Analytics.
By default, Google Analytics is enabled. Changes to this setting
only take effect after you reload the page.
For Vertex AI and Cloud Logging project, enter the name for the
Google Cloud project ID that you want to use for your assessment.
To use the Google Cloud project where you created your
Mainframe Assessment Tool VM, leave this field blank.
Optional: For Model, select a Gemini AI model.
By default, Mainframe Assessment Tool uses either Gemini 2.0 Flash-Lite
or Gemini 2.0 Flash, with Gemini 2.0 Flash
used adaptively to optimize performance. You can configure Mainframe Assessment Tool
to use a different model from the following available options:
Gemini 2.0 Flash
Gemini 2.0 Flash-Lite
Gemini 2.5 Pro
Gemini 2.5 Flash
If you run large assessments and change the default model, we recommend that
you increase the quota for that model to help enable faster assessment
completion. To adjust quotas, use the Google Cloud console. For more information, see
Request a quota adjustment.
Mainframe Assessment Tool supports all zones in all the
Vertex AI regions.
To control the creativity of the model's output, select Custom temperature
and set a value between 0.0 and 1.0.
By default, Mainframe Assessment Tool uses a value of 0.1. For more information,
see Model parameters.
Click Save settings.
Configure default AI features for new assessments
Mainframe Assessment Tool lets you customize the default parameters for AI insights
in your assessments. By default, AI insights are enabled.
To configure AI features in new assessments, follow these steps:
Click the settingsSettings
icon.
To generate paragraph-level summaries for COBOL code, select
Detailed summaries.
By default, this option is selected when AI analysis is enabled.
To generate test cases for the assessment specifications generated by
Gemini, select Test cases.
By default, this option is not selected when AI analysis is enabled.
To generate output code samples suggesting translation from mainframe
languages to Python, Java, C#, and SQL, select Code suggestions.
For Tech stack hints, enter text that helps
Gemini generate code for a specific tech stack. For example,
enter Spring Boot and MySQL.
Click Save settings.
Optional: Perform actions
This section describes how to perform actions, such as clearing the
Gemini cache and verifying connectivity to Gemini.
To perform actions, follow these steps:
Click the settingsSettings
icon.
To test your connectivity from Mainframe Assessment Tool to Google Cloud
services, click Verify connectivity.
If the connection is successful, you see a message similar to the following:
Connectivity success.
To clear the Gemini cache, click Clear model cache.
To download your Mainframe Assessment Tool logs, click Download support bundle.
The support bundle contains the Mainframe Assessment Tool logs as a zip file,
which you can share with Google Cloud support to troubleshoot issues.
Disable AI insights for assessments
Disabling AI analysis prevents AI insights from appearing on the
Assessments page.
To disable AI analysis for assessments, follow these steps:
In the Default AI features in new assessments section, clear
Enable AI insights.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,["# Configure settings\n\nThis page describes how to configure general Mainframe Assessment Tool settings\nand modify default AI features for new assessments.\n\nThe modified settings don't apply to existing assessments. To use modified\nsettings, create a new assessment.\n\nConfigure general settings\n--------------------------\n\nTo configure general settings for your assessment, follow these steps:\n\n1. Click the settings**Settings** icon.\n\n2. To edit your preferences for Cloud Logging and Google Analytics,\n in the **General settings** section, do the following:\n\n - To enable Logging, click **Enable Cloud Logging**.\n\n By default, Cloud Logging is disabled. Using Cloud Logging might incur\n additional costs. For more information, see [Cloud Logging\n documentation](/logging/docs).\n - To enable Google Analytics, click **Enable Google Analytics**.\n\n By default, Google Analytics is enabled. Changes to this setting\n only take effect after you reload the page.\n3. For **Vertex AI and Cloud Logging project**, enter the name for the\n Google Cloud project ID that you want to use for your assessment.\n\n To use the Google Cloud project where you created your\n Mainframe Assessment Tool VM, leave this field blank.\n | **Note:** Mainframe Assessment Tool uses Vertex AI in the region where the Mainframe Assessment Tool VM is deployed.\n4. Optional: For **Model**, select a Gemini AI model.\n\n By default, Mainframe Assessment Tool uses either Gemini 2.0 Flash-Lite\n or Gemini 2.0 Flash, with Gemini 2.0 Flash\n used adaptively to optimize performance. You can configure Mainframe Assessment Tool\n to use a different model from the following available options:\n - Gemini 2.0 Flash\n - Gemini 2.0 Flash-Lite\n - Gemini 2.5 Pro\n - Gemini 2.5 Flash\n\n If you run large assessments and change the default model, we recommend that\n you increase the quota for that model to help enable faster assessment\n completion. To adjust quotas, use the Google Cloud console. For more information, see\n [Request a quota adjustment](/docs/quotas/help/request_increase).\n\n Mainframe Assessment Tool supports all zones in all the\n [Vertex AI regions](/vertex-ai/generative-ai/docs/learn/locations#available-regions).\n5. To control the creativity of the model's output, select **Custom temperature**\n and set a value between `0.0` and `1.0`.\n\n By default, Mainframe Assessment Tool uses a value of `0.1`. For more information,\n see [Model parameters](https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters).\n6. Click **Save settings**.\n\nConfigure default AI features for new assessments\n-------------------------------------------------\n\nMainframe Assessment Tool lets you customize the default parameters for AI insights\nin your assessments. By default, AI insights are enabled.\n\nTo configure AI features in new assessments, follow these steps:\n\n1. Click the settings**Settings**\n icon.\n\n2. To generate paragraph-level summaries for COBOL code, select\n **Detailed summaries**.\n\n By default, this option is selected when AI analysis is enabled.\n3. To generate test cases for the assessment specifications generated by\n Gemini, select **Test cases**.\n\n By default, this option is not selected when AI analysis is enabled.\n4. To generate output code samples suggesting translation from mainframe\n languages to Python, Java, C#, and SQL, select **Code suggestions**.\n\n5. For **Tech stack hints** , enter text that helps\n Gemini generate code for a specific tech stack. For example,\n enter `Spring Boot and MySQL`.\n\n6. Click **Save settings**.\n\nOptional: Perform actions\n-------------------------\n\nThis section describes how to perform actions, such as clearing the\nGemini cache and verifying connectivity to Gemini.\n\nTo perform actions, follow these steps:\n\n1. Click the settings**Settings**\n icon.\n\n2. To test your connectivity from Mainframe Assessment Tool to Google Cloud\n services, click **Verify connectivity**.\n\n If the connection is successful, you see a message similar to the following:\n `Connectivity success`.\n3. To clear the Gemini cache, click **Clear model cache**.\n\n | **Note:** To improve performance and accuracy for subsequent assessments on the same files, don't clear the cache. Gemini uses the cache data for subsequent assessments.\n4. To download your Mainframe Assessment Tool logs, click **Download support bundle**.\n\n The support bundle contains the Mainframe Assessment Tool logs as a zip file,\n which you can share with Google Cloud support to troubleshoot issues.\n\nDisable AI insights for assessments\n-----------------------------------\n\nDisabling AI analysis prevents AI insights from appearing on the\n**Assessments** page.\n\nTo disable AI analysis for assessments, follow these steps:\n\n1. In the **Default AI features in new assessments** section, clear\n **Enable AI insights**.\n\n2. Click **Save settings**.\n\nWhat's next\n-----------\n\n- Learn how to [create an assessment](/mainframe-assessment-tool/docs/perform-assessment)."]]
