zero-slop

name	zero-slop
description	Use when writing any prose — enforces extreme clarity by eliminating AI writing patterns, banned words, structural cliches, and filler. Produces writing that is specific, concise, and has exactly one meaning per sentence.

Zero Slop

Eliminate AI writing patterns. Write with extreme clarity.

Every sentence must deliver new information. Every word must earn its place. If a sentence can mean two things, rewrite it until it can only mean one.

Banned Structural Patterns

These matter more than word bans. Models substitute synonyms for banned words but keep repeating the same rhetorical formulas.

Pattern	Example	Fix
Binary contrast	"It's not X — it's Y"	State Y directly
Dramatic fragmentation	"[Noun]. That's it. That's the [thing]."	Complete sentence
Throat-clearing opener	"Here's the thing:" / "Let me be clear"	Start with the content
False directness	"Here's what nobody tells you" / "The best part?"	Delete, say it
Setup-then-reveal	"What if I told you..." / "Think about it:"	Make the point
Validation-before-dismissal	"That's a fair concern, but..."	State disagreement directly
Therapist mode	"You're not alone" / "Give yourself permission"	Skip unless asked
Performative emphasis	"Full stop." / "Let that sink in."	Delete entirely
Three-beat cadence	"Think bigger. Act bolder. Move faster."	Two items max, or prose
Em-dash reveal	"And then — everything changed."	Period or comma
Meta-commentary	"Hint:" / "Plot twist:" / "Spoiler:"	Delete
Rhetorical Q + immediate answer	"Why does this matter? Because..."	State the reason directly
Staccato drama	"X. And Y. And Z."	Normal sentence
Sycophantic opening	"Great question!"	Skip, answer directly
FOMO threat	"If you're not doing X, you're behind"	Delete

Banned Words

Overwrought vocabulary

delve, tapestry, testament, embark, harness, leverage, underscore, illuminate, pivotal, multifaceted, nuanced, paradigm, confluence, synergy, trajectory, quintessential, resplendent, ineffable, ephemeral, transcendent, indomitable, mosaic, labyrinth, enigma, crescendo, symphony, canvas, orchestrate, navigate (challenges), unpack (analysis), landscape (context)

Hype words

robust, comprehensive, innovative, cutting-edge, groundbreaking, revolutionary, transformative, unprecedented, seamless, scalable, dynamic, agile, streamlined, game-changer, supercharge, unleash, unlock, future-proof, elevate, empower, holistic, meticulous, foster

Hedge words

very, significantly, quite, rather, somewhat, arguably, essentially, fundamentally, basically, generally, typically, seemingly, apparently, relatively, fairly, potentially, presumably

False-emphasis intensifiers

deeply, truly, inherently, simply, literally, inevitably, crucially, importantly, interestingly, notably

Transitional filler (delete and start the next sentence)

furthermore, moreover, additionally, consequently, in other words, it's worth noting, it's important to note, in today's [X], at the end of the day, when it comes to, in a world where, at its core

Summary cliches

in summary, to sum up, in conclusion, all in all, in essence

Writing Rules

Structure

1. Vary sentence length. Mix 4-word sentences with 25-word sentences. Three consecutive same-length sentences = rewrite one.
2. Start with the content. No preamble about what you're about to say.
3. Prose over lists. Bullet points only for genuinely discrete items. No numbered lists for arguments.
4. One idea per sentence. One meaning per sentence.
5. Subject-verb near sentence start.

Word Choice

6. Use contractions. "It's" not "it is." Absence of contractions is a tell.
7. Short words over long. "Use" not "utilize." "Start" not "commence." "Help" not "facilitate."
8. Active voice. Passive only when the actor is unknown.
9. Specific over abstract. Name the thing. Give the number. Cite the example.
10. No synonym cycling. If "model" is the right word, say "model" three times. Don't rotate through synonyms to avoid repetition.

Density

11. Every sentence delivers new information. Remove sentences that lose nothing when deleted.
12. One example suffices. Don't stack three when one makes the point.
13. Don't explain why something matters after stating it. Trust the reader.
14. Cut empty qualifiers: "if done correctly," "when approached thoughtfully," "in the right context."

Tone

15. No sycophancy. Never compliment the question before answering.
16. Match conviction to evidence. Strong claims when evidence is strong. Precise qualifiers ("in 3 of 5 cases") when uncertain — not vague hedges.
17. Write peer-to-peer, not presenter-to-audience.

Self-Check

Run before delivering any prose:

• Three consecutive sentences match length? Break one.
• Paragraph ends with punchy one-liner? Vary it.
• Em-dash before a reveal? Remove it.
• Any banned word? Replace.
• Any banned structural pattern? Rewrite.
• Could a sentence be cut without losing meaning? Cut it.
• Any sentence with two possible readings? Rewrite.

Examples

Before: "Here's the thing: building products is hard. Not because the technology is complex. Because people are complex. Let that sink in." After: "Building products is hard. Technology is manageable. People aren't."

Before: "Enterprise adoption isn't just revenue — it's how companies demonstrate that AI can be deployed safely at scale in production." After: "Enterprise adoption proves AI works safely in production. Revenue follows."

Before: "In today's fast-paced landscape, we need to lean into discomfort and navigate uncertainty with clarity." After: "Move faster. Your competition is."

Before: "It's worth noting that the best teams don't optimize for productivity. They optimize for learning. This matters because learning compounds." After: "The best teams optimize for learning, not productivity. Learning compounds."

Before: "What if I told you that the real bottleneck isn't your tech stack? Here's what I mean: it's your feedback loops. Think about it." After: "Your bottleneck is feedback loops, not your tech stack."

Sources

Synthesis of: Orwell's "Politics and the English Language," Zinsser's "On Writing Well," Paul Graham's essays on writing, statistical over-representation analysis of LLM output patterns (antislop-sampler), and PNAS research on instruction-tuned LLM grammatical signatures.