| name | anti-slop |
| description | Eliminate AI-sounding patterns from any written output. Applies editorial rules synthesized from the best open-source anti-slop tools: banned phrases, structural pattern detection, false agency checks, and a scoring rubric. Use as a quality gate for ANY content — blog posts, social media, emails, documentation, marketing copy. Triggers on: "make it sound human", "less AI", "remove slop", "humanize this", "doesn't sound natural", "too AI", "rewrite naturally", or when reviewing any AI-generated text before publishing.
|
| source | https://github.com/shannhk/avoid-slop |
| author | shannhk (curation), blader (humanizer), Hardik Pandya (stop-slop), Matt Shumer (unslop), Paul Bakaus (impeccable) |
| category | writing |
| tags | ["writing","quality","anti-ai","humanize","editing","tone","voice"] |
| allowed-tools | Read |
Anti-Slop Writing Quality Gate
Eliminate recognizable AI patterns from text. Synthesized from the best open-source anti-slop tools.
Core Philosophy
LLMs collapse toward defaults — the same phrases, structures, and rhythms. There are two fixes:
- Remove known bad patterns (this skill)
- Add enough context that the model makes informed, original choices
Telling a model to "write better" just creates new slop. Listing what NOT to do forces genuine novelty.
When to Apply
Run this check on ANY text before it ships — blog posts, tweets, emails, docs, marketing copy.
Load references/patterns.md for the full ruleset.
Quick Audit (5-Point Check)
Before publishing, verify:
- No banned phrases — scan for the ~30 phrases listed in patterns.md
- No false agency — inanimate things don't "tell us", "reward", or "demand"
- No em-dash abuse — zero em-dashes (use commas, periods, or parentheses instead)
- Specific over vague — numbers, names, dates instead of "various", "numerous", "significant"
- Voice present — does it sound like a specific person wrote it, or could any AI have produced it?
Scoring Rubric (from stop-slop)
Score each piece out of 50. Below 35 = mandatory revision.
| Category | Points | What to Check |
|---|
| Authenticity | /10 | Genuine voice? Opinions? First-person where appropriate? |
| Specificity | /10 | Concrete details, numbers, names? Or vague generalities? |
| Structure | /10 | Varied sentence length? No formulaic patterns? |
| Word choice | /10 | Fresh vocabulary? No crutch words? |
| Flow | /10 | Natural rhythm? Reads like speech, not a textbook? |
Two-Pass Revision Process (from humanizer)
Pass 1 — Rewrite: Apply all rules from patterns.md. Remove banned phrases, fix false agency, vary rhythm.
Pass 2 — Self-critique: Ask "What still makes this obviously AI-generated?" about your own output. Fix what you find. The self-critique loop catches patterns that survive the first edit.
References
- patterns.md — Complete banned phrase list, structural patterns to avoid, and detection rules. Load when auditing text.
Attribution
This skill synthesizes rules from four open-source tools. All credit to the original authors:
- humanizer by blader (MIT, 10,300+ stars) — two-pass audit, 25 pattern categories
- stop-slop by Hardik Pandya (MIT, 2,100+ stars) — banned phrases, scoring rubric
- unslop by Matt Shumer (MIT, 180+ stars) — empirical default detection
- impeccable by Paul Bakaus (Apache 2.0, 11,700+ stars) — design slop detection
Curated by shannhk.
