It bothers me that you have to explicitly state this to the agent. Makes me think what else is missing from that file which also needs to be explicitly stated, but I don't know what don't know. "Do a good job"?
Imagine you’re blind and deaf and have temporary retrograde amnesia. You “wake up” one moment with a memory of some words in your head like “what is the bug?” …but you don’t recall the context of that question, and nor can you look/listen around to observe the context.
So you don’t know whether you’re e.g. at the office, in front of your computer, in the middle of doing some pair-programming (where, yes, you’d in investigate the bug thoroughly with tools), vs. having a conversation with a colleague over lunch (where the expectation is for you to tap into your knowledge + intuitions to either guess or say you don’t know — not to pull out your laptop.
That’s what it’s like to be one of these LLMs being prompted by some agent harness. Unless the harness injects the proper context into its “recent memory”, it just doesn’t know.
As usual, if you use anything but the best model available I’m going to state that the better ones do better. If you do use the best model available, then I’ll just mention that Fable still has limits and still needs some guidance.
One thing it does not do is deliberately build tests which test nothing at all, or which restate the code under test. I mention this because certain other models absolutely would.
They will mock things to no end. They will flat out REMOVE assertions (saying it's not needed). They can also write test to assert the wrong result.
You have to always review it, it's exhausting.
Claude will do some boneheaded things for sure, but it's pretty good about writing tests that are useful, and not removing or modifying tests just because they're in the way.
Claude is pretty bad about assuming that it couldn't have broken a test it didn't know about, as it has often told me "this is already broken on main" which is definitely NOT true.
And I think I know why - neither do most people.