TICKET MANAGEMENT

ClickUp bug enrichment from linked Sentry issue

When a bug task references a Sentry issue, pulls the stack trace, breadcrumbs, and affected release into the ticket, then re-scores reproducibility with that evidence attached.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerBug task created or updated in ClickUpClickUpClickUp
  • LogicExtract Sentry issue reference
  • ActionFetch issue trace and release from SentrySentrySentry
  • ActionSummarize evidence and re-score reproducibilityOpenAI
  • OutputWrite enriched summary back to ClickUp taskClickUpClickUp

What it does

Many bug reports paste only a one-line symptom but link or mention a Sentry issue. This workflow detects that link, fetches the real diagnostic payload from Sentry — stack trace, breadcrumbs, affected release, and event count — and attaches it as a structured comment on the ClickUp task. It then re-scores reproducibility so a report that looked thin gets credit for the hard evidence Sentry already captured.

When to use it

Use it when engineers waste time hopping between ClickUp and Sentry to understand a bug, or when otherwise-vague reports are actually well-instrumented in your error tracker. It pulls the evidence to where triage happens.

How it works

  1. 1A new or updated bug task in ClickUp triggers the flow.
  2. 2A logic step extracts a Sentry issue ID or URL from the description.
  3. 3If found, the workflow fetches that issue's details from Sentry.
  4. 4OpenAI summarizes the trace and recomputes a reproducibility score using the Sentry evidence.
  5. 5The enriched summary and new score are written back as a ClickUp comment, and the task is tagged "sentry-enriched".

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ClickUpDocs + tasks + chats in one workspace.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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