Open-source AI text humanizers and slop detectors — strip 'delve', 'tapestry', em-dash clusters, and other AI tells. Code, prose, and academic modes.
Anti-Slop tools are AI-powered software designed to help developers and teams tackle anti-slop-related tasks more efficiently. These tools are typically published as open-source projects on GitHub and can be integrated into existing workflows via MCP (Model Context Protocol), Claude Skills, or standalone agent frameworks. On Agent Skills Hub, we index 30 quality-scored anti-slop tools across languages including JavaScript, Python, HTML.
In 2026, the AI agent ecosystem is maturing rapidly. Anti-Slop tools can significantly boost development efficiency by automating repetitive tasks, reducing human error, and providing intelligent suggestions. The top 3 tools — taste-skill, humanizer, Humanizer-zh — have earned an average of 5,639 GitHub stars, reflecting strong community validation. 25 of the listed tools come with clear open-source licenses, ensuring freedom to use and modify.
When choosing a anti-slop tool, consider these factors: 1) Community activity — GitHub stars and recent commit frequency indicate reliability; 2) Integration method — check if it supports MCP, Claude, or your preferred agent framework; 3) Language compatibility — the most common language in this list is JavaScript; 4) Quality score — Agent Skills Hub's composite score evaluates code quality, documentation completeness, and maintenance activity. Our recommendation: start with taste-skill — it ranks highest in both star count and quality score.
Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop
Agent skill that removes signs of AI-generated writing from text
```bash
mkdir -p ~/.claude/skills
git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer
```
Humanizer 的汉化版本,Claude Code Skills,旨在消除文本中 AI 生成的痕迹。
AI writing skill that eliminates detectable AI patterns. Works with Claude Code, Codex, Cursor, Gemini CLI, and 8+ other agents.
A Claude Code skill that removes signs of AI-generated writing from academic medical papers, making them sound more natural and professionally written.
```bash
mkdir -p ~/.claude/skills
git clone https://github.com/matsuikentaro1/humanizer_academic.git ~/.claude/skills/humanizer_academic
```
Open-source Agent Skill that scores AI-sounding writing 0–100, edits it with your assistant.
Make AI output sound human. Strips AI-isms (sycophancy, stock vocab, hedging stacks, em-dash pileups), preserves code/URLs/headings. Plugin for Claude Code, Cursor, Windsurf, Codex, Cline, Copilot, Gemini.
Best static AI text humanizer. Two research-grounded LLM-agnostic skills that make AI writing sound human and relatable. Nine levers, 50+ peer-reviewed sources, 2024-2026 detection literature.
33 ways to spot AI-written text, right in your terminal. Before/after examples, draft checker, zero dependencies.
text-humanizer is an open-source project designed to convert text generated by AI to its "humanized" version. Bypasses the most of AI detectors such as Turnitin or GPTZero
Structured plan/execute/verify coding workflow for Claude Code: atomic commits, MCP-backed state, ~92% lower per-turn token overhead, native convention + drift-detection safeguards, and an ASD-STE100 (Simplified Technical English) anti-slop docs gate. A Claude Code-native evolution of GSD and VibeDrift.
Open-source text humanization pipeline with every intermediate step published. Two LLM rewrites at temp 1.3, then two hops across different NMT engines. Four documented methodologies you can read, modify, and run locally.
免费本地 AI 文本去痕迹工具 | Chinese AI text detection & humanization. N-gram perplexity analysis, 20+ detection patterns, academic AIGC reduction (知网/维普/万方), 7 style transforms. Zero dependencies, runs locally.
Free, open-source AI writing humanizer and detector. 55 patterns, 5 voices, a 0-100 AI-tell score, and nothing leaves your machine.
去AI味 skill for Codex: a compact Chinese AI writing humanizer for AI味清理, template sentence shells, and fake engagement endings.
说人话|中文优先的去 AI 味改写 skill:保事实、分场景、改完可直接发。Chinese-first rewrite skill for Codex / Claude Code / Cursor / ChatGPT — removes AI tone, preserves facts.
The Claude Code skill that directs a website like a film. Commit-sheet, generated assets, build, and an executable anti-slop linter that gates every ship.
Make your agents talk human. ADHD-friendly output styles for Claude Code, Codex, and others. So you can pay attention, not tokens.
Türkçe metinlerden yapay zekâ yazım imzalarını temizleyen Claude skill'i. YZ üretimi Türkçe'yi doğal, insan-sesli Türkçe'ye dönüştürür. | A Claude skill that removes AI writing signatures from Turkish text.
Design engineering system for AI coding agents — ship UI with craft-level quality. Install as an agent skill.
Stop your AI from writing like AI. A universal system prompt eliminating every known LLM style tell — works with Claude Code, Gemini CLI, Codex CLI, Copilot, Cursor, and any web AI.
Make AI-generated prose sound human. 29-pattern catalog + 8-rule operating system + 8-dimension scoring rubric. Works with Claude Code, OpenCode, Copilot CLI, Codex, Gemini, Goose.
A local detector for AI-writing patterns. Scores every prose file your agent saves. Python standard library only, no network, no model.
Deutscher Text-Humanizer für Claude Code & Codex. Redigiert KI-Floskeln, schützt deine Schreibstimme und prüft 72 deutsche Muster quellentreu.
De-AI writing skill for any Agent Skills-compatible agent (77+ via the Skills CLI), with native plugins for Claude Code, Codex, Grok Build, and Antigravity. Narrative-architecture repair for fiction, venue-matched rules for professional prose. Based on StoryScope (arXiv:2604.03136).
Opinionated Oxlint rules for rejecting low-evidence TypeScript and JavaScript patterns
Two-pass pipeline for removing AI writing tells from outward-facing text: a surface pass plus a structural pass grounded in the StoryScope study. Packaged as Claude Code Skills. Free community: skool.com/jens-ai-community-1306
Self-evolving second brain with 35 AI skills, 10 agents, and people CRM. Closed-loop harness: a V-model verification lifecycle where the worker never grades its own homework. Plus paired anti-slop design skills for marketing and product UI. Works with Claude Code, Cursor, Kiro, Gemini CLI, Codex.
去除中文文本中 AI 写作痕迹的 Agent Skill(基于 blader/humanizer 与 op7418/humanizer-zh)
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| taste-skill | ★ 87.7k | JavaScript | MIT | 85 |
| humanizer | ★ 44.3k | Python | MIT | 88 |
| Humanizer-zh | ★ 17.6k | — | MIT | 64 |
| anti-ai-slop-writing | ★ 323 | — | — | 65 |
| humanizer_academic | ★ 181 | — | — | 74 |
| ZeroSlop | ★ 118 | Python | MIT | 55 |
| unslop | ★ 101 | Python | MIT | 67 |
| humanize | ★ 347 | HTML | MIT | 70 |
| humanizer-cli | ★ 569 | JavaScript | MIT | 81 |
| text-humanizer | ★ 494 | Python | MIT | 78 |
| buildomator | ★ 88 | TypeScript | MIT | 54 |
| humanize-text | ★ 3.0k | Python | MIT | 70 |
| humanize-chinese | ★ 305 | Python | — | 57 |
| humanizer-skill | ★ 218 | JavaScript | MIT | 71 |
| remove-ai-flavor-writing-skill | ★ 197 | Python | MIT | 67 |
| shuorenhua | ★ 1.8k | Python | MIT | 68 |
| auteur | ★ 1.0k | JavaScript | MIT | 75 |
| attention-span | ★ 979 | Python | AGPL-3.0 | 66 |
| turkce-humanizer | ★ 64 | — | MIT | 60 |
| ui-craft | ★ 309 | JavaScript | MIT | 71 |
| anti-slop-writing | ★ 110 | — | MIT | 71 |
| tagore | ★ 53 | Shell | MIT | 59 |
| patina | ★ 358 | JavaScript | MIT | 72 |
| sloptrim | ★ 210 | Python | Apache-2.0 | 61 |
| humanizer-de | ★ 154 | Python | — | 71 |
| sepia | ★ 2.7k | Python | MIT | 75 |
| anti-slop | ★ 4.3k | TypeScript | MIT | 82 |
| humanizer-stack | ★ 235 | Python | — | 70 |
| COG-second-brain | ★ 1.2k | HTML | MIT | 70 |
| humanizer-zh-next | ★ 80 | — | MIT | 62 |
The top anti-slop tools in 2026 are taste-skill, humanizer, Humanizer-zh. Agent Skills Hub ranks 30 options by GitHub stars, quality score (6 dimensions including completeness, examples, and agent readiness), and recent activity. The list is rebuilt every 8 hours from live GitHub data.
taste-skill (87.7k stars) is the most adopted choice for general anti-slop workflows, written in JavaScript. humanizer (44.3k stars) is a strong alternative and uses Python instead. Pick by your existing stack: match the language and runtime your team already uses to minimize integration cost. If unsure, start with taste-skill — it has the deepest community and the most examples online.
Avoid pre-built anti-slop tools when (1) your use case requires deep customization that the tool's plugin system doesn't support, (2) you have strict compliance requirements that ban third-party dependencies, (3) the tool's maintenance is inactive (last commit >6 months ago), or (4) your data volume is small enough that a 50-line custom script is cheaper than learning the tool. For most production workflows above 100 requests/day, the time savings from a maintained tool outweigh the customization loss.
For most teams, yes. taste-skill has 87.7k stars worth of community testing, handles edge cases you haven't thought of, and ships with documentation. Build your own only when (1) your requirements are deeply non-standard, (2) you have a security/compliance reason to avoid OSS dependencies, or (3) the maintenance burden is small enough (<200 lines of code) that you'll save time long-term. The break-even point is usually around 2-3 weeks of dev time saved.
Most anti-slop tools listed are open source under permissive licenses (MIT, Apache 2.0). A handful offer paid managed/cloud versions on top of free self-hosted core. Always check the LICENSE file on each tool's GitHub repository before commercial use — some use AGPL or non-commercial restrictions that may not fit your deployment model.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: