score-ai-sloplisted
Install: claude install-skill SalZaki/antislop
# Score AI Slop
Give the author a quality-pass read: how much slop is here, by category, and is it ready
to publish. This is the aggregate view over the same engine that `detect-ai-slop` and
`remove-ai-slop` use. It does not rewrite, and it does not return a single 0-10 number;
a headline score becomes a thing people optimize against, so the output stays a
breakdown plus a plain-language readiness call.
Rules, categories, severity, and the override-merge order live in
[`../../shared/spec.md`](../../shared/spec.md). Read it before scoring.
## How to score
**Deterministic tier (preferred).** Run the bundled script and use its `summary` (the
per-category counts) plus its `findings` for the breakdown:
```bash
python3 shared/slop_count.py --file <path> \
[--allow-list ~/.claude/config/remove-ai-slop/user-allow-list.md] \
[--allow-list .claude/skills/remove-ai-slop/overrides/user-allow-list.md] \
[--extra-vocab ~/.claude/config/remove-ai-slop/user-vocabulary.md] \
[--extra-vocab .claude/skills/remove-ai-slop/overrides/user-vocabulary.md]
```
Pipe text on stdin instead of `--file` when the user pasted it. Pass whichever override
files exist. The script is the sole override parser; consume its output, do not
re-parse the override tables.
**Judged tier (you).** The script cannot see meaning. Add a short note per
meaning-dependent category from the spec (`padding-and-filler`, `elegant-variation`, and
contextual cases). Mark these `judged`.
## Fallback — when `python3` i