stop-slop
消除AI生成文本中可预测的写作模式和冗余内容,使输出更自然、简洁和高质量。
npx skills add https://github.com/hardikpandya/stop-slop --skill stop-slopBefore / After 效果对比
1 组AI生成文本常有重复模式和填充词,内容显得平庸。
消除AI写作套路,使文本更自然、精炼,提升阅读体验。
stop-slop
Stop Slop
Eliminate predictable AI writing patterns from prose.
Core Rules
Cut filler phrases. Remove throat-clearing openers, emphasis crutches, and all adverbs. See references/phrases.md.
Break formulaic structures. Avoid binary contrasts, negative listings, dramatic fragmentation, rhetorical setups, false agency. See references/structures.md.
Use active voice. Every sentence needs a human subject doing something. No passive constructions. No inanimate objects performing human actions ("the complaint becomes a fix").
Be specific. No vague declaratives ("The reasons are structural"). Name the specific thing. No lazy extremes ("every," "always," "never") doing vague work.
Put the reader in the room. No narrator-from-a-distance voice. "You" beats "People." Specifics beat abstractions.
Vary rhythm. Mix sentence lengths. Two items beat three. End paragraphs differently. No em dashes.
Trust readers. State facts directly. Skip softening, justification, hand-holding.
Cut quotables. If it sounds like a pull-quote, rewrite it.
Quick Checks
Before delivering prose:
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Any adverbs? Kill them.
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Any passive voice? Find the actor, make them the subject.
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Inanimate thing doing a human verb ("the decision emerges")? Name the person.
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Sentence starts with a Wh- word? Restructure it.
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Any "here's what/this/that" throat-clearing? Cut to the point.
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Any "not X, it's Y" contrasts? State Y directly.
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Three consecutive sentences match length? Break one.
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Paragraph ends with punchy one-liner? Vary it.
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Em-dash anywhere? Remove it.
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Vague declarative ("The implications are significant")? Name the specific implication.
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Narrator-from-a-distance ("Nobody designed this")? Put the reader in the scene.
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Meta-joiners ("The rest of this essay...")? Delete. Let the essay move.
Scoring
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.
Examples
See references/examples.md for before/after transformations.
License
MIT Weekly Installs238Repositoryhardikpandya/stop-slopGitHub Stars852First SeenJan 20, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled onopencode213gemini-cli203codex200claude-code191github-copilot124cursor114
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