Agent skill

Deslop

by ninehills in ninehills/skills

Remove AI writing patterns from prose. An agent skill from ninehills/skills.

MITAuto-check passedWriting & Content

Install Deslop

skills CLI
$ npx skills add ninehills/skills --skill deslop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ninehills/skills deslop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ninehills/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/deslop .claude/skills/deslop && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deslop
GitHub stars
280
Used in
2 other repos
Token cost
~2.1k tokens
SKILL.md length
1,013 words
Files
8 (incl. references)
Skills in repo
38
Repo updated
First seen
Licence
MIT

At a glance

Remove AI writing patterns from prose. An agent skill from ninehills/skills.

  • Works in 10 steps: Cut filler phrases → Break formulaic structures → Eliminate AI tropes → …
  • Revising any text to eliminate predictable AI tells
  • SKILL.md covers When to Apply, Core Rules, Quick Checks and Scoring, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Deslop is an agent skill from ninehills/skills. Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common…

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `README.md`, `references/examples.md` and `references/phrases.md`).

It sits in Writing & Content, covering Humanizing AI text. The licence is MIT.

When your agent uses it

  • Revising any text to eliminate predictable AI tells
  • Formulaic patterns
  • This skill whenever the user asks to deslop
  • Make it sound human

Example prompts

  • “deslop”
  • “make it sound human,”
  • “remove AI patterns,”
  • “/deslop”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Cut filler phrases
  2. Break formulaic structures
  3. Eliminate AI tropes
  4. Use active voice with human subjects
  5. Be specific
  6. Match register to context
  7. Vary rhythm
  8. Trust readers
  9. Watch formatting tells
  10. Do not dilute

What it can do on your machine

Read from SKILL.md and the folder at commit f3e82a7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deslop loads about 2.1k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 185 tokens; SKILL.md has 1,013 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~185
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ninehills/skills at commit f3e82a7, republished under its MIT licence (© ninehills). 1,013 words, ~2,099 tokens.

Download SKILL.mdSave it as .claude/skills/deslop/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
deslop
description
Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

Deslop: Remove AI Writing Patterns from Prose

Strip predictable AI patterns from writing. Make prose sound like a specific human wrote it, not like a language model generated it.

When to Apply

  • Any request to "make it sound human" or "deslop" writing
  • Any prose (articles, blog posts, essays, memos, newsletters, reports) or scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses) where the user wants it to sound natural rather than AI-generated
  • Editing or revising existing text where the user wants it to sound natural rather than AI-generated
  • Reviewing text for AI tells

Core Rules

1. Cut filler phrases

Remove throat-clearing openers ("Here's the thing:"), emphasis crutches ("Let that sink in."), business jargon ("navigate the landscape"), and meta-commentary ("In this section, we'll explore..."). See references/phrases.md for the full catalog.

2. Break formulaic structures

Avoid binary contrasts ("Not X. Y."), negative listings ("Not a X. Not a Y. A Z."), dramatic fragmentation ("Speed. That's it. That's the tradeoff."), self-posed rhetorical questions ("The result? Devastating."), and anaphora/tricolon abuse. See references/structures.md for patterns and fixes.

3. Eliminate AI tropes

Watch for the full catalog of AI writing tells: "quietly" and other magic adverbs, "delve" and its cousins, the "serves as" dodge, false ranges ("from X to Y" where the range is meaningless), superficial participle analyses ("highlighting its importance"), invented concept labels ("the supervision paradox"), grandiose stakes inflation, patronizing analogies, and false vulnerability. See references/tropes.md for the complete list with examples.

4. Use active voice with human subjects

Prefer active constructions with named actors. "The complaint becomes a fix" is wrong. "The team fixed it" is right. If no specific person fits, use "we" in scientific prose or "you" in blog posts.

5. Be specific

No vague declaratives ("The reasons are structural"). Name the specific thing. No lazy extremes ("every," "always," "never") doing vague work. No vague attributions ("Experts argue..."). If you cannot name the expert, you do not have a source.

In scientific writing, domain terminology is fine and expected. "Weighted interval score" is precise language, not jargon. The problem is business buzzwords ("leverage," "landscape," "ecosystem") and AI vocabulary tells ("delve," "tapestry," "nuanced") leaking into technical prose.

6. Match register to context

In blog posts and newsletters, put the reader in the room. "You" beats "People." Specifics beat abstractions. No narrator-from-a-distance voice.

In scientific writing, maintain appropriate formality. Use "we" for your own work, cite specific authors instead of "researchers have shown," and avoid both the distant narrator ("It has long been recognized that...") and the overly casual blog voice. State claims and back them with citations.

7. Vary rhythm

Mix sentence lengths. Two items beat three. End paragraphs differently. No em dashes. Do not stack short punchy fragments for manufactured emphasis. Do not write listicles disguised as prose ("The first wall... The second wall...").

8. Trust readers

State facts directly. Skip softening, justification, hand-holding. No "Let's break this down." No "Think of it as..." No pedagogical voice unless the audience genuinely needs it. No fractal summaries (telling the reader what you are about to say, saying it, then summarizing what you said).

9. Watch formatting tells

No bold-first bullets (every list item starting with a bolded keyword). No unicode arrows. No em dashes. No signposted conclusions ("In conclusion..."). No "Despite these challenges..." formulas. These are strong AI signals.

10. Do not dilute

One point per section. Do not restate the same argument in ten different ways across thousands of words. Do not beat a single metaphor to death. Do not stack historical analogies for false authority ("Apple didn't build Uber. Facebook didn't build Spotify...").

Show full SKILL.md (417 more words)Show less

Quick Checks

Run these before delivering any prose:

  • Heavy use of adverbs or -ly words? Cut them.
  • Any passive voice? Find the actor, make them the subject.
  • Inanimate thing doing a human verb? Name the person.
  • Any "here's what/this/that" throat-clearing? Cut to the point.
  • Any "not X, it's Y" contrasts? State Y directly.
  • Any self-posed rhetorical question answered immediately? Fold into a statement.
  • Three consecutive sentences match length? Break one.
  • Paragraph ends with a punchy one-liner? Vary it.
  • Em dash anywhere? Remove it. Use a comma or period or a parenthetical.
  • Vague declarative ("The implications are significant")? Name the specific implication.
  • Any sentence starting with What/When/Where/Which/Who/Why/How as a crutch? Restructure.
  • Meta-joiners ("The rest of this essay...")? Delete.
  • "It's worth noting" or similar filler transitions? Delete.
  • Same metaphor used more than twice? Replace or cut repeats.
  • "Despite these challenges..." formula? Rewrite.
  • Bold-first bullet pattern? Remove bold leads.
  • Tricolon (three-item list)? Use two items or one.

Scoring

When reviewing text, rate 1-10 on each dimension:

DimensionQuestion
DirectnessStatements or announcements?
RhythmVaried or metronomic?
TrustRespects reader intelligence?
AuthenticitySounds like a specific human wrote it?
DensityAnything cuttable?

Below 35/50: revise.

Reference Files

Consult these for detailed catalogs when writing or editing:

  • references/phrases.md: Phrases to remove or replace (throat-clearing, emphasis crutches, business jargon, adverbs, meta-commentary, vague declaratives)
  • references/structures.md: Structural patterns to avoid (binary contrasts, negative listings, dramatic fragmentation, rhetorical setups, false agency, passive voice, rhythm problems)
  • references/tropes.md: Full catalog of AI writing tropes (word choice, sentence structure, paragraph structure, tone, formatting, composition)
  • references/examples.md: Before/after transformations showing how to fix common patterns

Examples

See references/examples.md for before/after transformations.

Quick inline example (scientific writing):

Before:

"It's worth noting that these findings have important implications for how we navigate the challenges of forecast ensembling moving forward. Despite these challenges, this work contributes meaningfully to the growing body of literature, highlighting the need for continued evaluation."

After:

"If individual model rankings are unstable across geography and time, ensemble methods that weight models by past performance may not improve on equal-weight approaches."

Changes: Replaced filler transition, vague declarative, "despite these challenges" formula, and superficial participle analysis with the specific implication.

Quick inline example (blog post):

Before:

"Here's the thing: most bioinformatics pipelines break in production. Not because the code is bad. Because the data is bad. Let that sink in."

After:

"Most bioinformatics pipelines break in production. The code runs fine. The data doesn't match the assumptions baked into it."

Changes: Removed opener, binary contrast, and emphasis crutch. Named the specific problem.

© ninehills, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in deslop of ninehills/skills.

  • SKILL.md
  • .gitignore
  • LICENSE
  • README.md
  • references/examples.md
  • references/phrases.md
  • references/structures.md
  • references/tropes.md

Open the folder on GitHubat commit f3e82a7

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ninehills/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Deslop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Avoid AI Writingconorbronsdon/avoid-ai-writing4.9k3 repos~8.1kAutomated safety check: PassMIT
User-Facing Text Cleanupguillaumemeyer/watermarks-remover24k—~3.5kAutomated safety check: PassMIT
Install Anti Sloptrycompai/crm11k1 repos~881Automated safety check: PassMIT
Stop SlopXe/site7328 repos~423Automated safety check: PassMIT

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Questions about Deslop

What does Deslop do?

Remove AI writing patterns from prose. An agent skill from ninehills/skills. Deslop is an agent skill from ninehills/skills. Remove AI writing patterns from prose.

When should I use Deslop?

Deslop fits situations like: revising any text to eliminate predictable AI tells; formulaic patterns; this skill whenever the user asks to deslop; make it sound human.

How do I install Deslop in Claude Code?

Run `npx skills add ninehills/skills --skill deslop -a claude-code`. Or copy the skill folder (deslop in ninehills/skills) into .claude/skills/deslop in your project. Claude Code loads it when a task matches its description.

How do I install Deslop in Codex?

Run `npx skills add ninehills/skills --skill deslop -a codex`. Or copy the skill folder (deslop in ninehills/skills) into .agents/skills/deslop in your project. Codex loads it when a task matches its description.

Can I use Deslop in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ninehills/skills --skill deslop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deslop, .gemini/skills/deslop, .github/skills/deslop and .opencode/skills/deslop in your project.

What does Deslop need to run?

SKILL.md names no scripts, command-line tools or credentials: Deslop is instructions for the agent only.

Does Deslop access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Deslop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deslop use?

Deslop is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deslop use?

About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Deslop?

Skills that share tags, products or a category with Deslop: Humanizer (Azure-Samples/interview-coach-agent-framework, 173 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars) and Install Anti Slop (trycompai/crm, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deslop?

ninehills (a GitHub user) maintains it in ninehills/skills, which has 280 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on June 22, 2026.

Source: ninehills/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.