ENGINEERING
Agent Triages a Flaky Test and Drafts a Root-Cause Hypothesis
An AI agent pulls the failing run's logs and recent diffs, classifies the likely flake cause (timing, ordering, network, fixture), and posts a root-cause hypothesis…
How it runs
The automated pipeline, trigger to output.
- TriggerNew Linear issue tagged flaky-testLinear
- ActionFetch failing job logs and stack trace from GitHubGitHub
- ActionPull recent diffs touching the test fileGitHub
- ActionAgent classifies cause and drafts root-cause hypothesisOpenAI
- OutputComment analysis and confidence label on Linear issueLinear
What it does
Turns a bare "this test is flaky" ticket into an actionable investigation. An agent reads the failure logs, stack trace, and the recent commits touching the test, then categorizes the most probable cause and drafts a concrete fix suggestion — so the assigned engineer starts with a hypothesis instead of a blank page.
When to use it
Use it when flaky-test tickets pile up uninvestigated because triage is tedious. This front-loads the diagnostic work the moment a flake is filed.
How it works
- 1A new Linear issue tagged `flaky-test` triggers the workflow.
- 2An action fetches the failing GitHub Actions job logs and stack trace.
- 3An action pulls the recent commits and diffs touching the test file.
- 4An agent reasons over logs and diffs to classify the flake (timing, test ordering, network, shared fixture) and drafts a root-cause hypothesis with a suggested fix.
- 5An output posts the analysis as a comment on the Linear issue and assigns a confidence label.
Set it up
What you configure once, before turning it on.
- 1Connect LinearIssues, projects, cycles, triage.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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