Beginner~12 min setupAI & CommunicationVerified April 2026
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How to Summarize Slack Threads with OpenAI Using Make

Automatically generate thread summaries in Slack by reacting with πŸ“ emoji - Make calls OpenAI API and posts the summary as a reply.

Steps and UI details are based on platform versions at time of writing β€” check each platform for the latest interface.

Best for

Teams that need instant AI summaries of long Slack discussions with custom formatting and multi-channel support.

Not ideal for

Simple use cases that only need summaries in one channel or teams comfortable building custom Slack bots.

Sync type

real-time

Use case type

notification

Real-World Example

πŸ’‘

A 25-person product team uses this to summarize lengthy feature discussions in #product-reviews. Before automation, the PM manually read through 15+ message threads daily and wrote recap notes for stakeholders. Now team members just react with πŸ“ on important threads and get AI summaries within 10 seconds. The bot processes about 40 threads per week, saving 2 hours of manual review time.

What Will This Cost?

Drag the slider to your expected monthly volume.

/mo
505005K50K

Each platform counts differently β€” Zapier: 1 task per trigger. Make: 1 operation per module per record. n8n: 1 execution per run.

Prices shown for annual billing. Based on published pricing as of April 2026.

Estimated ROI

1000

min saved/mo

$583

labor value/mo

Free

no platform cost

Based on ~2 min manual effort per operation at $35/hr fully loaded labor cost.

Implementation

Skip the setup

Import this workflow directly into Make

Copy the pre-built Make blueprint and paste it straight into Make. All modules, filters, and field mappings are already configured β€” you just need to connect your accounts.

Before You Start

Make sure you have everything ready.

Slack workspace with admin permissions to add bots
OpenAI API account with available credits
Make account (free tier works for low volume)
Channels where you want thread summarization enabled

Optional

Team awareness that πŸ“ emoji triggers the bot

Field Mapping

Map these fields between your apps.

FieldAPI Name
Required
Channel IDchannel
Message Timestampts
Thread Messagesmessages[].text
Message Authorsmessages[].user
AI Prompt Textprompt
Summary Responsechoices[].text
Reply Thread IDthread_ts

Step-by-Step Setup

1

Dashboard > Create Scenario > Add Module > Slack

Create New Scenario in Make

Start building your thread summarization workflow. Make will watch for specific emoji reactions in Slack channels.

  1. 1Click 'Create a new scenario' from your Make dashboard
  2. 2Click the blue '+' button to add your first module
  3. 3Search for 'Slack' in the app list
  4. 4Select 'Watch Reactions Added' trigger
βœ“ What you should see: You should see a Slack module with 'Watch Reactions Added' as the selected trigger type.
2

Slack Module > Connection > Add

Connect Slack Account

Authenticate Make to access your Slack workspace. You'll need admin permissions to read message content and reactions.

  1. 1Click 'Add' next to Connection field
  2. 2Select 'OAuth 2.0' connection type
  3. 3Click 'Continue' and authorize Make in the Slack popup
  4. 4Choose your workspace from the dropdown
βœ“ What you should see: Green 'Connected' status appears with your workspace name displayed.
⚠
Common mistake β€” Make sure your Slack app has 'channels:history' and 'reactions:read' scopes - the default OAuth includes these.
Make settings
Connection
Choose a connection…Add
click Add
OpenAI
Log in to authorize
Authorize Make
popup window
βœ“
Connected
green checkmark
3

Slack Module > Configure

Configure Reaction Trigger

Set the trigger to fire only when someone adds the πŸ“ emoji. This prevents the automation from running on every reaction in your workspace.

  1. 1Select specific channels or leave blank for all channels
  2. 2In the 'Reaction' field, type 'memo' (the emoji code for πŸ“)
  3. 3Set 'Limit' to 1 to process one reaction at a time
  4. 4Click 'OK' to save the trigger configuration
βœ“ What you should see: The Slack trigger shows 'memo' in the reaction field and your selected channels.
⚠
Common mistake β€” Use 'memo' not the actual πŸ“ emoji - Make needs the text code, not the Unicode character.
Make
+
click +
search apps
OpenAI
OP
OpenAI
Configure Reaction Trigger
OpenAI
OP
module added
4

Add Module > Slack > Get Thread

Add Slack Get Thread Module

Fetch the complete thread conversation. This module retrieves all messages in the thread so OpenAI has the full context to summarize.

  1. 1Click the '+' button after your reaction trigger
  2. 2Search for 'Slack' and select 'Get Thread'
  3. 3Use the same connection from step 2
  4. 4Map 'Channel' field to the trigger's channel ID
  5. 5Map 'Timestamp' field to the trigger's message timestamp
βœ“ What you should see: Get Thread module shows mapped channel and timestamp fields from the previous trigger.
⚠
Common mistake β€” Don't confuse 'Get Thread' with 'Get Message' - you need the thread version to capture replies.
5

Add Module > Tools > Text Aggregator

Add Text Aggregator

Combine all thread messages into a single text block. OpenAI needs one continuous text input, not separate message objects.

  1. 1Click '+' and search for 'Text aggregator'
  2. 2Select 'Text aggregator' from Tools category
  3. 3Set 'Source Module' to the Get Thread module
  4. 4In 'Text' field, map: {{2.messages[].user}}: {{2.messages[].text}}
  5. 5Set 'Row separator' to line break (\n)
βœ“ What you should see: Text aggregator shows the Get Thread module as source with the user/text mapping formula.
⚠
Common mistake β€” Include the user names in your aggregation - OpenAI provides better summaries when it can distinguish speakers.
6

Add Module > OpenAI > Create a Completion

Add OpenAI Module

Connect to OpenAI's API to generate the thread summary. This module sends the aggregated text and receives the AI-generated summary.

  1. 1Click '+' and search for 'OpenAI'
  2. 2Select 'Create a Completion' action
  3. 3Click 'Add' next to Connection
  4. 4Paste your OpenAI API key in the API Key field
  5. 5Click 'Save' to establish the connection
βœ“ What you should see: OpenAI module appears with 'Create a Completion' selected and green connection status.
⚠
Common mistake β€” Get your API key from platform.openai.com/api-keys - don't use your ChatGPT login credentials.
7

OpenAI Module > Configure

Configure OpenAI Completion

Set up the AI prompt and parameters for thread summarization. The model and temperature settings control summary quality and consistency.

  1. 1Set Model to 'gpt-3.5-turbo-instruct'
  2. 2In Prompt field, enter: 'Summarize this Slack conversation in 2-3 bullet points:\n{{5.text}}'
  3. 3Set Max Tokens to 150
  4. 4Set Temperature to 0.3 for consistent summaries
  5. 5Leave other fields at default values
βœ“ What you should see: OpenAI module shows your prompt template with the aggregated text variable mapped.
⚠
Common mistake β€” Keep temperature low (0.1-0.3) for summaries - higher values make the AI too creative and inconsistent.
8

Add Module > Slack > Create a Message

Add Reply Module

Post the AI summary back to the original Slack thread. This creates a threaded reply so the summary appears in context.

  1. 1Click '+' and add another Slack module
  2. 2Select 'Create a Message' action
  3. 3Use existing Slack connection
  4. 4Map Channel to the original trigger channel
  5. 5Map Thread Timestamp to the trigger's message timestamp
βœ“ What you should see: Slack message module configured to reply in the same channel and thread as the original reaction.
9

Slack Message Module > Configure

Format Summary Message

Create the final message format with the AI summary. Add context so users know this is an automated summary.

  1. 1In the Text field, enter: 'πŸ€– Thread Summary:\n{{6.choices[].text}}'
  2. 2Set 'Parse Mode' to 'none'
  3. 3Enable 'Unfurl Links' if you want link previews
  4. 4Leave 'As User' disabled to post as the bot
βœ“ What you should see: Message module shows the summary template with OpenAI response mapped to the text field.
⚠
Common mistake β€” Use thread timestamp from the trigger, not the Get Thread module - otherwise replies go to the wrong message.
Message template
πŸ“¬ New entry: {{1.name}}
Email: {{1.email}}
Details: {{1.description}}
10

Right-click OpenAI Module > Add Error Handler

Add Error Handling

Configure what happens when OpenAI is unavailable or rate limited. This prevents the scenario from breaking on API errors.

  1. 1Right-click the OpenAI module
  2. 2Select 'Add error handler'
  3. 3Choose 'Break' directive
  4. 4Add a Slack message module in the error path
  5. 5Set error message: 'Sorry, I couldn\'t generate a summary right now. Please try again later.'
βœ“ What you should see: Error handler route appears below OpenAI module with Break directive and fallback message.
11

Scenario > Run Once

Test the Scenario

Run a test to verify the complete workflow. Make will simulate a real emoji reaction and show you each step's output.

  1. 1Click 'Run once' at the bottom left
  2. 2Go to Slack and add πŸ“ reaction to a test thread
  3. 3Return to Make and watch the execution progress
  4. 4Check each module's output in the execution log
  5. 5Verify the summary appears in your Slack thread
βœ“ What you should see: All modules show green checkmarks and the AI summary appears as a threaded reply in Slack.
⚠
Common mistake β€” Test on a thread with 3+ messages - single messages don't need summaries and may confuse the AI.
Make
β–Ά Run once
executed
βœ“
OpenAI
βœ“
Slack
Slack
πŸ”” notification
received
12

Scenario > Schedule > ON

Enable Automatic Scheduling

Turn on the scenario to run continuously. Make will now monitor all reactions in real-time and generate summaries automatically.

  1. 1Click the 'OFF' toggle in the bottom left corner
  2. 2Select 'Immediately' for the schedule
  3. 3Click 'OK' to confirm activation
  4. 4The toggle should now show 'ON' with a green indicator
βœ“ What you should see: Scenario status shows 'ON' and 'Immediately' with green active indicator.
⚠
Common mistake β€” Start with 'Immediately' scheduling - don't use intervals for reaction triggers since they're event-based.

Drop this into a Make custom function.

JavaScript β€” Custom Function{{if(length(5.text) > 2000; left(5.text; 2000) + "\n[Thread truncated - showing first 2000 characters]"; 5.text)}}
β–Έ Show code
{{if(length(5.text) > 2000; left(5.text; 2000) + "\n[Thread truncated - showing first 2000 characters]"; 5.text)}}

... expand to see full code

{{if(length(5.text) > 2000; left(5.text; 2000) + "\n[Thread truncated - showing first 2000 characters]"; 5.text)}}

Scaling Beyond 50+ summaries per day+ Records

If your volume exceeds 50+ summaries per day records, apply these adjustments.

1

Add Request Delay

Insert a 2-3 second delay before the OpenAI module to avoid rate limits. OpenAI allows 60 requests per minute on paid accounts.

2

Batch Processing

Consider collecting multiple thread requests and processing them in batches during off-peak hours. Use Make's data store to queue requests.

3

Model Optimization

Switch to gpt-3.5-turbo with chat format instead of text completion. It's 10x cheaper and handles longer threads without hitting token limits.

Going live

Production Checklist

Before you turn this on for real, confirm each item.

Troubleshooting

Common errors and how to fix them.

Frequently Asked Questions

Common questions about this workflow.

Analysis

VerdictWhy Make for this workflow

Use Make for this if you need real-time thread summarization across multiple Slack channels and want granular control over the AI prompts. Make's visual builder makes it easy to modify the summarization logic, add filters for specific channels, or chain additional actions like saving summaries to a database. The webhook-based triggers fire instantly when someone adds the emoji reaction. Skip Make and use a simple Slack bot instead if you only need basic summarization in 1-2 channels.

Cost

This workflow consumes about 8 operations per run - 1 for the trigger, 2 for getting thread data, 1 for text aggregation, 2 for OpenAI API calls (including retries), and 2 for posting the summary. At 100 summaries per month, that's 800 operations total. Make's free tier includes 1,000 operations monthly, so you're covered. The Pro plan at $9/month gives you 10,000 operations. Zapier would cost $20/month for the same volume since their cheapest paid plan starts higher. N8n is free if self-hosted but requires server management.

Tradeoffs

Zapier has better error handling for OpenAI rate limits with built-in exponential backoff, while Make requires manual retry configuration. N8n offers more flexible text processing with JavaScript functions, letting you create more sophisticated prompts or filter out certain message types before sending to OpenAI. But Make wins on simplicity and has the most reliable Slack webhook triggers - both competitors occasionally miss reactions during high Slack activity periods.

You'll hit OpenAI's rate limit at around 50 concurrent requests, so add a 2-second delay module if your team uses this heavily. Slack's thread timestamp format changes between different message types - permalink reactions use different timestamps than direct message reactions, which will break your thread mapping. The text aggregator has a 32KB limit, so threads longer than about 200 messages will get truncated before reaching OpenAI.

Ideas for what to build next

  • β†’
    Add Summary Analytics β€” Track which channels use summarization most and measure time saved. Connect a Google Sheets module to log usage data.
  • β†’
    Create Topic-Specific Prompts β€” Set up different scenarios for #support, #sales, and #product channels with customized AI prompts for each context.
  • β†’
    Auto-Archive Long Threads β€” After summarization, automatically move threads older than 7 days to an archive channel to keep active channels clean.

Related guides

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