TICKET MANAGEMENT

Unclear-Resolution Macro Improver

Reviews reopened tickets caused by unclear resolutions, traces which Zendesk macro or canned reply was used.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionFetch unclear-resolution reopens with applied macro from ZendeskZendeskZendesk
  • LogicGroup by macro, keep those above reopen threshold
  • ActionDraft clearer macro rewrites with before/afterOpenAI
  • ActionAppend rewrite proposals to Notion review docNotionNotion
  • OutputPost proposals to content team Slack for approvalSlack

What it does

When customers reopen because the closing reply was confusing, the canned macro is often the culprit. This workflow finds those unclear-resolution reopens, identifies the macro behind them, and proposes a rewritten version — turning repeated confusion into a concrete content fix.

When to use it

Use it when your reopen problem is communication, not technical. If agents are solving correctly but customers keep coming back asking what to do next, your macros need work. Best for teams managing support content in Notion.

How it works

  1. 1A weekly schedule fires the run.
  2. 2Pull Zendesk tickets reopened within N days carrying the `unclear-resolution` cause tag, including the macro applied at solve time.
  3. 3A logic step groups reopens by the macro that produced them and keeps only macros above a reopen threshold.
  4. 4An OpenAI step rewrites each high-friction macro for clarity, with a before/after and the reasoning.
  5. 5Append each proposal to a Notion review doc for the knowledge owner.
  6. 6Post the list of proposed rewrites to the content-team Slack for approval.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  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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