System tools are built-in features that help Optimizely Opal take action. Each tool performs a specific task, such as creating a campaign, uploading files, or generating images. Think of tools like attachments on a Swiss Army knife. Each one has a distinct purpose that helps you get work done.
In addition to the system tools available in Opal, Optimizely Content Recommendations includes a set of system tools designed to help you find high-performing content items and topics and analyze recommendation widget performances.
Click a tool's name to expand it and learn when to use it, its required and optional parameters, and example prompts to calling the tool. If you do not provide a required parameter, Opal prompts you for it.
To enable the Content Recommendations tools, go to Connections > Content Recommendations and select one or more product instances. When you enter a prompt in Chat, select the instance from the Set Product Instance drop-down list to get data for that instance. You can access data for the past 30 days.
contentrecs_top_content – Retrieves the highest-performing content items ranked by user interactions within a specified date range. Helps identify which articles, posts, or content pieces resonate most with your audience.
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When to use
- Understand which content drives the most engagement.
- Identify successful content patterns and formats.
- Discover content worthy of promotion or repurposing.
- Measure content engagement rates.
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Parameters
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from_date– Start date in ISO 8601 (YYYY-MM-DD) format. -
to_date– End date in ISO 8601 (YYYY-MM-DD) format. -
limit– (Optional) Maximum number of results (10 – 1000, default: 200).
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Example prompts
- Show me the top-performing articles from last week.
- Could you please provide me with the top 5 articles for each month in 2025?
contentrecs_top_topics – Retrieves performance metrics for the most engaging topics based on user interactions. Identifies trending topics and reveals which topics resonate most with your audience.
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When to use
- Discover high-performing topics for content creation.
- Identify content gaps where popular topics are underrepresented or lack coverage.
- Find underperforming topics that need improved content quality.
- Guide content strategy decisions.
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Parameters
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from_date– Start date in ISO 8601 (YYYY-MM-DD) format. -
to_date– End date in ISO 8601 (YYYY-MM-DD) format. -
limit– (Optional) Maximum number of results (10 – 1000, default: 200).
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Example prompts
- What are the trending topics my audience engaged with in the last 30 days?
- Based on the previous month's data, what should we focus on writing next?
- Could you please provide me with the top 5 articles for each month in 2025?
contentrecs_top_recommendation_widgets – Analyzes recommendation widget performance with detailed A/B testing metrics comparing personalized and unpersonalized recommendations.
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When to use
- Evaluate ROI of recommendation strategies.
- Identify the widgets that benefit most from personalization.
- Optimize widget placement and configuration.
- Measure the lift from personalization investment.
- Make data-driven decisions on enhancing recommendation algorithms.
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Parameters
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from_date– Start date in ISO 8601 (YYYY-MM-DD) format. -
to_date– End date in ISO 8601 (YYYY-MM-DD) format.
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Example prompts
- How did our recommendation widgets perform last month?
- Could you please provide me with the top 5 articles for each month in 2025?
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