SOCIAL MEDIA

Legal-Threat Comment to Linear Triage

Detects comments that contain legal threats — defamation claims, cease-and-desist language, regulatory complaints — and opens a triaged Linear issue for the legal team with full…

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew comment received across platformsSocial publishing
  • ActionExtract legal-threat type and severityOpenAI
  • LogicFilter: keep only legal-risk matches
  • ActionCreate labeled Linear issue with due dateLinearLinear
  • OutputNotify legal team in Slack with issue linkSlack

What it does

This workflow narrows the firehose to one thing: comments that read like legal exposure. When a reply mentions lawsuits, lawyers, false-advertising, data-privacy violations, or refund disputes that imply regulatory risk, it files a structured Linear issue so legal can own it with a real SLA instead of a screenshot in a chat thread.

When to use it

Use it when your legal or trust-and-safety team needs an auditable paper trail for every comment that could escalate to a complaint or claim. Ideal for regulated industries — finance, health, supplements — where a public comment can trigger a formal obligation to respond.

How it works

  1. 1New comments arrive from connected social platforms.
  2. 2An LLM extracts whether the comment asserts a legal threat and what type (defamation, regulatory, contractual, privacy).
  3. 3A filter drops anything that is not a legal-risk match.
  4. 4A Linear issue is created in the legal team's project, labeled by threat type with severity and a due date.
  5. 5The team is notified in Slack with a direct link to the new issue.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Social publishingCross-post to X, LinkedIn, Instagram, TikTok, and 4 more in one call.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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