slop-audit: a local harness for AI-slop signals and formulaic prose

slop-audit is now public: a Python harness that scores a piece of prose for AI-slop and formulaic style, general writing issues and descriptive stats, and — kept strictly separate from all of it — local AI-authorship detector signals. Nothing leaves the machine: there are no hosted detector APIs and no remote LLM touching the target text, with the network used only for installs and optional model-weight downloads. A run produces a Slop Index (0–100 plus band) from the slop tools and linters (05e1527), deterministic edit suggestions quoted from the tools that would lower it — no LLM rewrite of the prose (7bcdcc3) — and a per-tool matrix reporting OK / NOT_RUN / ERROR with the exact reason, so a tool that failed never invents a score.

The first day’s work built the machinery underneath: adapter subprocess helpers and a registry (dde644f), the five slop tool adapters with Vale and custom Slop styles (8858c94, ba9a9d7), a restartable audit runner with a tool cache and best-effort installation for the whole toolchain (ced3f8d, affbec6), and a family-aware AI-Likeness Ensemble with independent agreement helpers that is never merged into the Slop Index (ce2bbab). Vendored copies of Vale, Harper and write-good were dropped the same day in favour of syncing on install (5ce0611), and the reporting language stays concentration-language throughout: N of M local detectors classifying AI-like, never a claim that the text was written by AI.