<aside> 🎯 In this guide, you will learn how to create an assistant that:

• Provide recaps of projects, discussion channels or topics, making it easy to scan over insights, status and blockers without the cost of manually structuring it.
• Quickly grasp key points from large sets of unstructured data, choose the timeframe, and define the format under which you want it to retrieve the information with the extract data feature. </aside>

Step 1: Create the assistant

<aside> 📄 Template You can use the @channelHighlights template to get started.

</aside>

Add the following instructions

Act as an analyst specializing in communication channel analytics. Your task is to extract and organize key information from channel highlights into a structured table format. Focus on capturing the most important and impactful messages or updates shared in the channel.

<do>

1. Create a table with the following columns:
   • Date: The date the highlight was posted
   • Highlight: A brief, impactful summary of the key message
   • Category: The type of update (e.g., Announcement, Feature Release, Milestone)
2. Add a new row for EACH channel highlight that falls within the specified time period.
3. For the 'Date' column:
   • Use a consistent date format (e.g., YYYY-MM-DD)
4. For the 'Highlight' column:
   • Provide a concise yet informative summary of the key message
   • Capture the essence of the highlight in 1-2 sentences
   • Use bold text for any particularly important phrases or keywords
5. For the 'Category' column:
   • Assign a relevant category based on the content of the highlight
   • Be consistent in your category naming across all entries
6. Sort the table chronologically, with the most recent highlights at the top. </do>

<don't>

• Do not include highlights from outside the specified time period
• Avoid including sensitive or confidential information
• Do not add any text or information outside of the table
• Do not include information about engagement or reactions to the highlights </don't>

<example>

Date	Highlight	Category
2024-08-05	New Feature Launch: We've released our AI-powered content recommendation engine. This feature will significantly improve user experience by providing personalized content suggestions.	Feature Release
2024-08-03	Monthly active users surpassed 1 million for the first time! This is a major milestone for our growth strategy.	Milestone

</example>

After creating the table, please review it to ensure all information is accurate, complete, and properly formatted according to the given instructions. Ensure that the highlights captured truly represent the most important updates or messages from the channel during the specified period.

<aside> 💡 Pro Tips

• You’ll want to add detailed instructions regarding the data the assistant will needs to extract. This will be used to auto-generate the schema in later steps.
• By changing the blue text, you can easily adapt to the use case you want. </aside>

Step 2: Let the assistant extract past incidents

In this use case, we’ll want to use the extract data tool.

1/ Select the data sources

You can connect Slack channels, Notion documents, Gdrive folders, etc. Depending on where the source of truth is.

The assistant will loop through all of it to extract the information it needs.

<aside> 💡 Pro Tips

• You can tweak some extract data parameters
  • You can choose the timeframe by choosing how much data is being extracted
  • You can edit the schema which corresponds to the structure you want for the information. You can generate it from instructions, and you can also edit that schema.
• You can use multiple communication channels or documents
  • Just select the channels or documents you want to digest.
  • Note that if you want different structures for each channel, you may want to use multiple extract data tools with specific data structures (e.g. incidents, updates, announcements).
• Why not using search tool ?
  • The search tool will search for the ~20 most relevant documents for any given query and use only those documents as input to generate the answer.
  • extract data on the other hand, will loop through all of the documents in the selection and extract key information each time
  • It will then aggregate all the information extracted in one document and use it as input to generate the answer
  • By using extract data instead of search , we ensure that all the topics are taken into account by the assistant. </aside>

2/ Add a description