When I give an AI coding agent a task, I never actually know if the context I sent it was enough. So I built the check.
The stack is four small tools, all Python standard library, all MIT, all local:
A fifth tool, ghostworkflow, runs the chain in one command, and a small local web app puts a face on it.
I ran the whole thing on its own repo and published the result warts and all: verdict attention, 2 verify gaps, and a test failure that turned out to be a path assumption in one of my own tests. The first dogfood run also caught a real bug in the contained runner (it hid the user site-packages, so pytest vanished), which is fixed and shipped.
I am looking for 5 to 10 developers who use AI coding agents daily to run it on one of their own repos and tell me where it breaks or bores them. Quickstart is 6 clones and one command. Links and the case study: https://gist.github.com/littlestjames82-sys/7e8309315c89706aefa97de6a4cc5399
What I want to know most: did the verify verdict match what your agent actually struggled with?