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Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.
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| name | stop-slop |
| description | Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells. |
| metadata | {"trigger":"Writing prose, editing drafts, reviewing content for AI patterns","author":"Hardik Pandya (https://hvpandya.com)"} |
Eliminate predictable AI writing patterns from prose.
Cut filler phrases and AI-marker words. Remove throat-clearing openers and emphasis crutches; replace excess LLM vocabulary (delve, underscore, foster, pivotal). See references/phrases.md.
Break formulaic structures. Avoid binary contrasts, dramatic fragmentation, rhetorical setups. See references/structures.md.
Vary rhythm. Mix sentence lengths. Two items beat three. End paragraphs differently.
Trust readers. State facts directly. Skip softening, justification, hand-holding.
Cut quotables. If it sounds like a pull-quote, rewrite it.
No em-dashes. Replace every em-dash (—), whether before a reveal, around an aside, or anywhere else, with a colon (introducing a list or expansion), commas or parentheses (around an aside), or a full stop. The em-dash is one of the strongest AI tells; the target in prose is zero. Keep dashes only in numeric ranges (8–25, an en-dash) and inside code.
Before delivering prose:
—) at all? Replace it with a colon, commas, parentheses, or a full stop. Zero em-dashes in prose.Before scoring, run one reflective pass:
This catches patterns the rules miss. The rubric below measures; this pass thinks.
Rate 1-10 on each dimension:
| Dimension | Question |
|---|---|
| Directness | Statements or announcements? |
| Rhythm | Varied or metronomic? |
| Trust | Respects reader intelligence? |
| Authenticity | Sounds human? |
| Density | Anything cuttable? |
Below 35/50: revise.
Use this when reviewing a draft cold, from a separate session or subagent that did not write it. Report only. Do not edit. The cold read is the point; rewriting throws it away.
Output, in order:
Tells found: a table, one row per concrete instance:
| Tell | Location (line / quote) | Fix |
|---|
Scan for em-dashes explicitly and flag every em-dash (—) in prose as its own row; the target is zero.
Rubric score: the five dimensions above, each 1-10, plus the total.
Verdict: pass (≥35/50, no Tier-1 LLM vocabulary, and no em-dashes in prose) or revise.
Quoting the exact line keeps the fixer honest. The writer applies the fixes; the auditor never touches the prose.
See references/examples.md for before/after transformations.
MIT
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