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You can lessen your dependence on the specific details of how /loop, code routines, etc. work by asking the LLM to do simpler tasks, and instead, having a proper workflow engine be in charge of the workflow aspects. For example, this demo (https://github.com/barnum-circus/barnum/tree/master/demos/co...) converts a folder of files from JS to TS. It's something an LLM could (probably) do a decent job of, but 1. not necessarily reliably, and 2. you can write a much more complicated workflow (e.g. retry logic, timeout logic, adding additional checks like "don't use as casts", etc), 3. you can be much more token efficient, and 4. you can be LLM agnostic. So, IMO, in the presence of tools like that, you shouldn't bother using /loop, code routines, etc. |
Straight up asking Claude to run the tests, or to generate a test, could result in potential inconsistencies between runs or between tests, between models, and so on, so instead he created a tool which defines a test, inputs and outputs and some details. Now we have a system where we have a directory full of markdown files describing a test suite, parameters, test cases, error cases, etc., and Claude generates the usage of the tool instead.
This means that whatever variation Claude, or any other LLM, might have run-to-run or drift over time, it all still has to be funneled through a strictly defined filter to ensure we're doing the same things the same way over time.