JevMade field notes / Architecture and workflow guide

Set strict limits on an AI assistant reviewing software code

This guide explains how to use a tool that forces an AI assistant to finish reviewing software code within strict limits. It shows how to set rules that give a clear pass or fail result.

Original by liuyanghejerryAgent workflows

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Credits and license

“Clausura” by liuyanghejerry. Read the original source.

This expanded guide is an AI-narrated adaptation of the source’s essential explanation, examples and caveats, not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

License: MIT

MIT License

Copyright (c) 2026 liuyanghejerry

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Our summary

Clausura is a tool that manages an AI assistant as it checks new software code for mistakes. People use it to automatically approve or reject changes before they are added to a main project, ensuring the software does not waste time running endless review loops.

The system gives the AI assistant strict limits on how long it can work and how many steps it can take. If the assistant finds mistakes, a separate rule checker decides if the project should pass or fail based on those specific findings.

This setup helps software teams that need reliable, automatic checks rather than open-ended conversations. It can use Jev, an AI tool that chooses from options rather than writing text, to double-check findings. If the assistant formats its answer badly, it only gets a few chances to fix it.

Key takeaways

Set separate limits for how long an AI assistant works and how many steps it takes.
Save the software's progress so you can figure out what went wrong if it stops unexpectedly.
Give the AI assistant a limited number of tries to fix a badly formatted answer.

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