SOCIAL MEDIA

React with a flag emoji to escalate a community thread to GitHub

When a teammate reacts to a forwarded community message in Slack with a flag emoji, an LLM analyzes the thread sentiment and root cause.

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFlag emoji reaction added in SlackSlack
  • ActionFetch the full Slack thread for contextSlack
  • ActionClassify sentiment and infer component with OpenAIOpenAI
  • LogicMap component to repo, labels, and assignee
  • ActionCreate labeled GitHub issue with permalinkGitHubGitHub
  • OutputReply in Slack thread with issue linkSlack

What it does

Lets your team escalate by reaction. When someone adds a flag emoji to a community message that was mirrored into a Slack channel, this reads the full thread, classifies the sentiment and likely root cause, and files a GitHub issue in the appropriate repository with the right labels and assignee, linking back to the source conversation.

When to use it

Use this when humans, not rules, decide what gets escalated, but you still want consistent, well-formed engineering tickets. A reaction is the lowest-friction signal; the workflow handles the rest of the paperwork and routing.

How it works

  1. 1A Slack reaction-added event fires when the flag emoji is used.
  2. 2The workflow fetches the full Slack thread for context.
  3. 3OpenAI classifies sentiment, summarizes the issue, and infers the likely component.
  4. 4A logic step maps the inferred component to a GitHub repo, labels, and assignee.
  5. 5GitHub creates an issue with the summary, sentiment, and Slack permalink.
  6. 6The bot replies in the Slack thread with the new issue link.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SlackChannels, DMs, threads, mentions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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