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.claude/skills/analyze-toxgen/SKILL.md

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@@ -36,13 +36,14 @@ will look like this: "py3.14t-openai_agents-v0.9.1: FAIL", while a passing
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one will look like this: "py3.14t-openai_agents-v0.9.1: OK".
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Compile a text summary that contains the following:
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- A list of all failing integrations.
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- A list of all failing integrations
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- For each integration:
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* The specific tox targets that are failing
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* The test failure message or error output from the failing tests
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* The command used in CI to run the test suite to reproduce the failure --
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it should use tox, check the job output for the specific command
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- Show the summary to the user.
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it should use the tox command (NOT pytest), check the job output for
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the specific command
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- Show the summary to the user
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### Step 2: Analyze failures
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#### Analyze non-flake failures
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Run the test suite for the failing tox target locally via `tox -e {tox_target}`.
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Run the test suite for the failing tox target locally via `tox -e {tox_target}`.
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Analyze the error message from the local run, then start localizing
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the source of the breakage:
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First check out the toxgen/update branch locally. Then branch off of it for the
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fix. When fixing, make sure the integration code supports both the current and
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the new way of integrating with the library, as we need to support both.
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After you're done fixing, if the user agrees that you should open a PR, open
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one with the toxgen/update branch as merge target. Include an analysis of the
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failure in the PR description. Include links to PRs or commits from the upstream
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library that introduced the relevant change.
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Poll the CI on the new branch and if there are failures, address them.

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