CHATBOTS

File a Linear doc-gap ticket when ReadMe can't answer

When the Discord bot finds no ReadMe page that answers a developer's question, it opens a deduplicated Linear ticket so the docs team can close the gap.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew developer question in DiscordDiscordDiscord
  • ActionSearch ReadMe and score answer coverageReadMeReadMe
  • LogicBranch on coverage below threshold
  • ActionCheck Linear for existing doc-gap ticketLinearLinear
  • ActionCreate deduplicated Linear doc-gap ticketLinearLinear
  • OutputAcknowledge gap logged in DiscordDiscordDiscord

What it does

Detects when a developer's Discord question has no good answer in ReadMe and turns that miss into a tracked Linear ticket for the docs team. It dedupes against open tickets so the same gap doesn't spawn duplicates, and it links the originating Discord message for context.

When to use it

Run this when you want unanswered questions to become a prioritized documentation backlog instead of disappearing into chat history. It converts community confusion directly into actionable work.

How it works

  1. 1A new Discord question triggers the run.
  2. 2The flow searches ReadMe for relevant pages and scores coverage.
  3. 3A branch checks whether coverage cleared the confidence threshold; if it did, the run ends with no ticket.
  4. 4For low-coverage misses, the flow searches Linear for an existing open ticket on the same topic.
  5. 5If none exists, it creates a Linear ticket tagged "docs-gap" with the question, suggested doc area, and Discord permalink.
  6. 6The bot posts a short acknowledgement in Discord noting the gap was logged.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DiscordCommunity channels + voice + bots.
  2. 2
    Connect ReadMeAPI docs, changelog, auth.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect OpenAIModels, embeddings, files.
  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.

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