unslop

unslop is a skill for Claude Code from jlwin/unslop_ai. It costs 238 tokens per session (11,185 once invoked), scanned A, original, MIT.

A writing and editing guide for German and English prose. It addresses word choice, sentence rhythm, and document structure to reduce patterns associated with machine-written text.

In plain words
What is it for?
Use it when writing or revising emails, posts, newsletters, articles, reports, presentations, biographies, press releases, and similar content.
Why use it?
Changing a few words may not fix writing that feels artificial. This guide also examines sentence patterns and the way ideas are organised.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the unslop plugin — 1 skill shipped together

Good fit Use it when writing or revising emails, posts, newsletters, articles, reports, presentations, biographies, press releases, and similar content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jlwin/unslop_ai/unslop
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add jlwin/unslop_ai --skill unslop
Clone the repo
git clone --depth 1 https://github.com/jlwin/unslop_ai

Made for: Claude Code.

Or install unslop, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for unslop

README.md
[![agentmods](https://agentmods.dev/badge/skills/jlwin/unslop_ai/unslop/github.svg)](https://agentmods.dev/skills/jlwin/unslop_ai/unslop)
Your own site
<a href="https://agentmods.dev/skills/jlwin/unslop_ai/unslop"><img src="https://agentmods.dev/badge/skills/jlwin/unslop_ai/unslop/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for unslop

Your own site · 80×15
<a href="https://agentmods.dev/skills/jlwin/unslop_ai/unslop"><img src="https://agentmods.dev/badge/skills/jlwin/unslop_ai/unslop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 238 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 11,185 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00238 $0.11185
Opus 5.5 $0.00095 $0.04474
Sonnet 5.5 $0.00048 $0.02237
Haiku 4.5 $0.00024 $0.01119

Measured 12d ago against content hash 134329c26cc2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

unslop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/unslop/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Unslop

Prevents and removes the patterns that make readers recognize text as AI-generated – in German and English. This file follows its own rules; the tells it quotes are data, not violations.

Core principle: three levels, one universal rule

AI slop lives on three levels. Swapping words alone achieves little: structural features by themselves identify AI text with over 93 % accuracy, and professional surface rewriting barely shifts detection (StoryScope 2026). Word lists also age with every model generation. So always work through all three levels, weighted toward 2 and 3:

  1. Word level – vocabulary, stock phrases, punctuation. The weakest but most visible signal. Lists: references/word-lists.md.
  2. Sentence and rhythm level – uniform sentence lengths, parataxis chains, triads, negative parallelisms, load-bearing metaphors, hedge stacking, copula avoidance.
  3. Structure level – the spelled-out takeaway, uniform paragraphs, template scaffolding, vague instead of named references, narrative arcs that explain and resolve everything, shape convergence across texts. The most durable signal.

The universal rule: swap the vague claim for the checkable fact. That means a figure, a name, a date, a price, or the mechanism behind the claim. „Deutlich schneller“ needs a sourced time comparison; „von 4 Klicks auf 1“ needs sourced click counts and does not itself prove a shorter duration. But when the concrete fact is missing, mark the gap; never invent a number, anecdote, or source. A made-up detail damages trust more than an honest gap.

The short version

When attention is scarce, use these ten checks:

  1. Swap vague claims for sourced, checkable facts; keep relative measures such as „halbiert“ at their original strength. Flag missing evidence rather than inventing it.
  2. Pick the register first (profile table below): the same rule can be right in one register and wrong in the next.
  3. State the core point once, except in summaries required by the register; every sentence adds information; no formulaic opener or generic closer.
  4. Vary sentence construction without staccato; avoid parataxis chains and decorative triads, keeping groups whose meaning has three parts.
  5. At most one rhetorical negative parallelism per piece, usually none; corrective instructions, corrected figures, and authenticity statements stay.
  6. Check word-list hits in context; apply tier thresholds and protected uses. Keep the punctuation budget (em dash: rare in prose, zero on slides).
  7. Prose: actor and verb early, the everyday word. Slides: sober nominal style.
  8. Headings and slide titles name the content, usually with noun labels; deliberate action titles carry checkable claims.
  9. Name things (sources, tools, dates); name feelings instead of performing them.
  10. Never add facts, persona, or staccato the source did not have.

Read the full file on GitHub · 260 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago Changed · +5 lines · +57 tokens per session 134329c26cc2
  2. 19d ago Changed · +1 lines 948bf4ca774d
  3. 20d ago Changed · +12 lines c53c408497d4
  4. 23d ago Changed · +12 lines 42c4dd9fec1e
  5. 24d ago Changed · +7 lines 63b9aa643412
  6. 1mo ago First seen · 223 lines · 181 tokens per session scan A e58079ef8266

Subscribe to this mod's changes

unslop is a skill published in the GitHub repository jlwin/unslop_ai (4 stars, last pushed 12d ago), licensed MIT. It adds 238 tokens to every session and 11,185 once invoked, about $0.0010 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.