CUSTOMER SUPPORT

Rewrite Help Articles That Get Repeated Negative Feedback

Watches help-center article feedback for pages that accumulate "not helpful" votes, reads the failing article plus related tickets to find what readers actually needed.

CategoryCustomer Support
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires
  • LogicFlag articles over the negative-vote threshold
  • ActionFetch the flagged article body from ReadMeReadMeReadMe
  • ActionPull recent tickets on the same topicZendeskZendesk
  • ActionDraft an improved rewrite with a change summaryOpenAI
  • OutputSave ReadMe draft and post diff to review channelSlack

What it does

A gap is not always a missing article, sometimes it is a bad one. This workflow monitors article feedback and flags any page that crosses a threshold of "not helpful" votes in a window. It then reads the failing article alongside recent tickets about the same topic to understand what readers were missing, drafts an improved rewrite in ReadMe, and routes it for editorial review with a diff summary.

When to use it

Use it when articles exist but are not landing, leaving customers to file tickets anyway. Instead of waiting for a manual content audit, this catches underperforming docs from the feedback signal and proposes a concrete fix grounded in the questions the article failed to answer.

How it works

  1. 1A daily schedule starts the run.
  2. 2Pull article feedback counts and flag pages over the negative-vote threshold.
  3. 3For each flagged page, fetch the current article body from ReadMe.
  4. 4Pull recent tickets tagged to the same topic for missing context.
  5. 5Use OpenAI to draft an improved rewrite plus a summary of what changed.
  6. 6Save the rewrite as a ReadMe draft and post the diff to the docs review channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ReadMeAPI docs, changelog, auth.
  2. 2
    Connect ZendeskTickets, queues, knowledge base.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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.

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