ENGINEERING

Agent-Drafted Flaky-Test Cleanup Plans from JUnit Reports

Receives a JUnit results webhook, has the CEO agent classify each flaky failure by likely root cause, and files an owner-assigned ClickUp task with a proposed fix plan.

CategoryEngineering
EngineSim + Paperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerJUnit report posted via webhookHTTP webhook
  • LogicParse report and isolate non-deterministic failures
  • ActionAgent classifies cause and drafts fix planOpenAI
  • ActionResolve owner from CODEOWNERSGitHubGitHub
  • OutputFile owner-assigned ClickUp cleanup task with planClickUpClickUp

What it does

This workflow adds reasoning to flaky-test triage. When your CI pipeline posts a JUnit report, an agent inspects the failure messages and stack traces, classifies the probable cause (timing, shared state, network, ordering), and drafts a concrete cleanup plan, then files an owner-assigned ClickUp task so the fix starts with a hypothesis instead of a blank page.

When to use it

Use it when raw flake counts are not enough and triagers waste time re-reading the same stack traces. It suits teams that want first-pass root-cause guesses and a starting fix plan attached to every quarantined test.

How it works

  1. 1An incoming webhook delivers the JUnit XML from a finished CI run.
  2. 2The flow parses the report and isolates non-deterministic failures (retried or intermittently failing cases).
  3. 3The agent reads each failure's message and trace, classifies the likely flake category, and proposes a remediation plan.
  4. 4It resolves the responsible owner from the repository's CODEOWNERS.
  5. 5It creates a ClickUp task per flake with the category, fix plan, and failing-test details assigned to that owner.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Connect ClickUpDocs + tasks + chats in one workspace.
  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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