My top four slop-fighting best practices for coding agents are below.
My overall observations (a) the way coding agents work right now, agents give unit tests too much authority, an bad tests are a huge source of slop (2) try to force your coding agent to simplify as much as possible on a goal, especially if it's possible to quantify the simplification
(1) @dillon_mulroy's antislop lint, conveniently available as an npm package - a bunch of oxlint rules designed to reject slop
(2) the "useless test deleter" from @_lopopolo- asks your agent to check for tests that are useless, and then refactor your code to stop being needlessly complex to conform to said useless tests
(3) Tell your AI "delete as much as possible" before finishing a change h/t @Secondmindsys
(4) adversarial goal on a slop metric such as LOC, halstead complexity, etc h/t @josephdviviano
Dowling recommends anti-slop lint rules as one mechanical check on patterns generated by coding agents.
He suggests examining whether tests provide useful evidence and whether accommodating weak tests has made the implementation needlessly complex.
His advice combines a final deletion pass with explicit complexity targets; these are workflow suggestions rather than evidence that fewer lines always improve software.
Why it matters
Tests can preserve unnecessary complexity when agents treat them as unquestionable requirements. Review what a test proves and ask for simplification alongside correctness checks.
