Globales Ranking · von 601 Skills
de-slopify AI Agent Skill
Quellcode ansehen: oakoss/agent-skills
SafeInstallation
npx skills add oakoss/agent-skills --skill de-slopify 42
Installationen
De-Slopify
Overview
De-slopify is a methodology for removing telltale signs of AI-generated content from documentation, prose, and code. LLMs produce statistically regular output with characteristic vocabulary, punctuation habits, and structural patterns that make text and code feel inauthentic. Some patterns appear over 1,000x more frequently in LLM output than human writing.
When to use: Before publishing READMEs, after AI-assisted writing sessions, during documentation reviews, when reviewing AI-generated code for over-engineering, before committing prose or code that an LLM touched.
When NOT to use: On code logic or algorithms where correctness matters more than style. On technical specifications where precision outweighs voice. On content that was already human-written and reads naturally.
Quick Reference
| Category | Pattern | Fix |
|---|---|---|
| Punctuation | Emdash overuse | Semicolons, commas, colons, or split into two sentences |
| Phrase | "Here's why" / "Here's why it matters" | Explain why directly without the lead-in |
| Phrase | "It's not X, it's Y" | "This is Y" or restate the distinction |
| Phrase | "Let's dive in" / "Let's get started" | Delete; just start the content |
| Phrase | "It's worth noting" / "Keep in mind" | Delete the hedge; state the fact |
| Phrase | "At its core" / "In essence" / "Fundamentally" | Delete; say the thing directly |
| Vocabulary | "delve", "tapestry", "landscape", "nuanced" | Replace with plain, specific language |
| Vocabulary | "revolutionize", "cutting-edge", "game-changer" | Replace with concrete claims or delete |
| Structure | Uniform sentence length throughout | Mix short (5-word) and long (20+ word) sentences |
| Structure | Perfectly balanced lists of exactly 3 items | Vary list length; humans use 2, 4, or odd counts |
| Structure | Generic claims without specifics | Add names, dates, numbers, or first-person detail |
| Sycophancy | "Great question!" / "Absolutely!" | Delete; answer the question directly |
| Meta | "Let me break this down..." / "Let me explain" | Delete the preamble; just break it down |
| Structure | Numbered lists where a sentence suffices | Use a sentence; reserve lists for genuinely parallel items |
| Closer | "In conclusion" / "To summarize" | Delete or replace with a specific takeaway |
| Code | Over-commented trivial functions | Remove comments that restate the code |
| Code | Unnecessary abstractions and design patterns | Flatten to the simplest working solution |
| Code | Verbose or overly descriptive variable names | Use domain-appropriate concise names |
| Code | Defensive error handling on every operation | Handle errors only where failure is realistic |
Common Mistakes
| Mistake | Correct Pattern |
|---|---|
| Replacing every emdash mechanically | Evaluate context; sometimes an emdash is the right choice |
| Editing code blocks for style | Focus on prose; leave code examples and technical syntax untouched |
| Removing all structure to sound casual | Keep headers, tables, and lists intact; rewrite prose only |
| Over-correcting into choppy fragments | Read aloud after editing; recombine sentences that lost flow |
| Applying fixes without defining target voice | Set persona, tone, and audience before starting edits |
| Running regex replacements instead of reading | Manual line-by-line review is required; context determines fixes |
| Ignoring AI code smells | Review AI-generated code for over-engineering, verbose names, and unnecessary abstractions |
| Removing all LLM-typical words unconditionally | Some flagged words are perfectly natural in context; use judgment |
Delegation
- Scan a repository for documentation files that need de-slopifying: Use
Exploreagent - Rewrite an entire documentation site to remove AI artifacts: Use
Taskagent - Plan a documentation voice guide and editorial workflow: Use
Planagent - Review AI-generated code for slop patterns: Use
code-revieweragent
For systematic quality auditing across 12 dimensions (architecture, security, testing, performance, etc.), use the
quality-auditorskill.
References
- Prose patterns: emdash alternatives, phrase replacements, and voice calibration
- Before-and-after examples of common AI writing fixes
- AI slop vocabulary: words and phrases that signal LLM authorship
- Code slop: detecting and fixing AI-generated code smells
- Review workflow: prompts, checklists, and integration
Installationen
Sicherheitsprüfung
Quellcode ansehen
oakoss/agent-skills
Mehr aus dieser Quelle
EU-Hosted Inference API Power your AI Agents with
the best open-source models.
Drop-in OpenAI-compatible API. No data leaves Europe.
Explore Inference APIGLM
GLM 5
$1.00 / $3.20
per M tokens
Kimi
Kimi K2.5
$0.60 / $2.80
per M tokens
MiniMax
MiniMax M2.5
$0.30 / $1.20
per M tokens
Qwen
Qwen3.5 122B
$0.40 / $3.00
per M tokens
So verwenden Sie diesen Skill
Install de-slopify by running npx skills add oakoss/agent-skills --skill de-slopify in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.
Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.
Der Skill verbessert das Verständnis Ihres Agenten für de-slopify, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.
Was Sie erhalten
Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.
Kompatibilität
Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.
Made in Europe Chat with 100+ AI Models in one App.
Use Claude, ChatGPT, Gemini alongside with EU-Hosted Models like Deepseek, GLM-5, Kimi K2.5 and many more.
