Unslop
A Claude skill that removes signs of AI writing from English text. Not just the word-level tells ("delve", "it's important to note") but the structural ones: over-explained conclusions, template paragraphs, invented specifics. Calibrates to your personal voice.
GitHub About line: "English text humanizer for Claude: typography, vocabulary, structure. Calibrates to your voice. Built on the UMD / Google DeepMind study and Wikipedia's Signs of AI writing."
Why word-swapping doesn't work
Every humanizer promises to make AI text "sound human", and most of them swap vocabulary: "delve" out, "explore" in. There are two problems with that.
First, the wordlist decays. "Delve" peaked in 2023 and collapsed in 2025. GPT-5.1 suppresses em dashes. Wikipedia's Signs of AI writing now dates its vocabulary lists by model era, because each generation retires the previous tells.
Second, and worse: the words were never the real signal. In 2026, the University of Maryland and Google DeepMind compared 61,608 texts written by humans and five models. When they ran AI texts through surface editing (clichés, purple prose, redundant exposition removed), a classifier looking only at structure barely noticed: detection dropped from 95.5% to 93.9%. The text gives itself away by how it's built. AI states the moral of every paragraph, runs single-track claim-support-takeaway structure, renders emotion through body metaphors, avoids naming real things, and rounds every ending to a tidy point.
A humanizer that only touches vocabulary fixes the layer that was already fixing itself, and leaves the durable signal intact. This skill works on three levels at once.
How it's built
Level 1: typography and mechanics. Em dashes, mixed quotation marks, Title Case Headings, bold on every "key term", inline-header bullet lists, "Conclusion" sections, markdown debris like utm_source=chatgpt.com. Cheap fixes; partially grep-checkable, and the skill greps itself.
Level 2: vocabulary and rhetoric. 19 categories of constructions with stop lists and fixes: inflated significance ("stands as a testament"), negative parallelisms ("it's not X, it's Y"), the rule of three, superficial -ing analysis ("...highlighting the importance of"), copula avoidance ("serves as" for "is"), synonym cycling, vague attributions, and more. Every category ships with a before/after. The AI wordlist is dated by model era, because it expires.
Level 3: structure and epistemics. The part that survives model updates. Don't chew conclusions. Break paragraph symmetry. Use real specifics, and only real ones: the skill forbids inventing numbers, examples, and thresholds for "liveliness", because invented specifics are worse than clichés: a cliché reads as filler, an invented fact reads as fact. Hedge once per limitation, not once per sentence. And a section most humanizers skip: what human writing is allowed to do. Plain "is" and "has". Plain verbs: wrote, used, died. Superlatives when true. Hedges when honest. These are the constructions AI avoids and people use freely; the skill protects them instead of sanding them off.
There's also a rule against replacement tics: any substitute phrase repeated across three texts becomes a new marker. The cure for a cliché is usually not another phrase but its absence.
Voice calibration
The default "human" tone is still someone else's. So the skill can become yours:
calibrate to my style
Claude asks for a few texts you wrote yourself, extracts a profile (em dash tolerance, pet connectives, sentence rhythm, the personal tics that must never be cleaned out, per-genre registers), and saves it to references/style-profile.md: plain markdown you can edit by hand. From then on, every edit lands on top of your voice, not on top of an averaged "good style".
Updates are incremental: "learn from this text too" appends to the profile instead of rewriting it.
What calibration will not do: enable invented facts, switch off the epistemics rules, or imitate another named author.
Field test
The first launch post for this skill was written with the skill active, posted to r/ClaudeAI, and identified as AI within the hour. The top comment: "run your skill on your slop post before posting or it didn't work at all." Fair. Users even quoted the giveaway lines back, and two of them wrote parody comments that agreed with the thesis while mocking the delivery.
The failure taught us something the 61,608-text study didn't: cleaning out GPT-isms leaves behind the model's own house style. Every sentence load-bearing, every paragraph landing on an aphorism, confidence perfectly uniform, and the whole document shaped like a launch-post template. Real people don't sustain that.
v1.1 is the fix: category 19 in the blacklist (clean slop: the punchy one-liner closings, "That's not X. That's Y.", verdict verbs, uniform confidence), an outline test in the final check (read the first sentence of every paragraph; if they form a tidy summary, the structure is machine-shaped), a slack rule (one or two sentences per text get to be ordinary), and a prose benchmark file derived from essays that do this well. If you find the next layer of residue, open an issue; that's how category 20 will get written.
Install
Claude.ai / Claude Desktop: Settings, Capabilities, Skills, upload unslop.skill (or the repo as a ZIP).
Claude Code:
git clone https://github.com/asavvin-pixel/unslop ~/.claude/skills/unslop
Use
The skill triggers on "humanize this", "unslop", "de-AI", "make it sound human", and when writing English text from scratch. Typical requests:
unslop this: [...]
write a post about [...] that doesn't read as generated
rewrite this section, keep the length and structure
calibrate to my style
Three edit modes: free (filler gets deleted, text may shrink), careful (structure and 80–110% of length survive, for fixed formats), minimal. The genre always survives: a post stays a post, an email stays an email.
Repo structure
unslop/
├── SKILL.md # the rules, three levels
├── examples/
│ └── mindfulness.md # full before/after with commentary
└── references/
├── blacklist.md # 19 stop-list categories with fixes
├── prose-benchmarks.md # what good plain prose measurably does
└── style-profile-template.md # calibration profile template
Sources
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Russell J. et al. StoryScope: Investigating idiosyncrasies in AI fiction. UMD / Google DeepMind, 2026. arXiv:2604.03136
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Format inspired by blader/humanizer
What it won't do
It doesn't try to beat AI detectors, and that's deliberate: detectors err in both directions, and text written to fool a detector is bad in its own way. The goal is text you're not embarrassed to show a person. It also won't replace the author: if the source has no facts in it, the output is an honest short text plus a list of what's missing, not a convincing imitation.
Russian version
For Russian text, use the sister skill ochelovech: Russian AI text has its own lexicon (bureaucratic calques, «является»-constructions, the letter «ё» as a tell), so wordlists don't translate. The structural level is shared; each skill adapts it to its language.