Who it is forA developer writing Jev Choice, Noul, or Score questions who wants to catch request errors before deploying them.
The problemA malformed question with missing options or a broken state reference can produce bad decisions that are hard to trace later.
The outcomeA question file that passes an offline lint check, ready to send to Jev through the TypeSafe Python SDK.
What you need first
- Access to Jev through TypeSafe, which the SDK and integration entries rely on
- Git and Python, since most picks in this list are Python or run from a repo
- Review of each project's permissions and data handling before running it, as the README asks
Steps
- Open the wellposed repository at https://github.com/suraj-phanindra/wellposed and read its README for how to run the linter.
- Read the official TypeSafe Skill at https://github.com/typesafe-ai/skills for guidance on writing Noul, Choice, and Score questions.
- Run the linter on your question file and note any findings for missing options, broken state references, or wrong question types.
- Fix each finding and rerun the linter until it reports no problems.
- Send the corrected question with the TypeSafe Python SDK at https://github.com/typesafe-ai/typesafe-sdk-python, which includes a support-ticket routing example.
Prompt for your agent
Use the wellposed repo (https://github.com/suraj-phanindra/wellposed) to lint the question file at <path-to-question-file>. Fix any missing options or broken state references it reports, then return the corrected file and the linter output. Verify that the linter now reports zero findings.
Caveat. The README describes wellposed only as an offline request linter, so check its own docs for exact usage before relying on it.
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Disclaimer
Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page