Neue Skills, Referenzen & OpenWiki-Doku integriert

Umfangreiche Erweiterung der Skill-Bibliothek: Neue Skills für Humanisierung (Englisch/PT-BR), Design-Validierung, AI-SEO und Coolify-Deployment inkl. Regelwerke, Presets, Pattern-Referenzen, Testfälle und Automatisierungsskripte. Zusätzliche Skills für Revenue-Centric Design, Pier Cloud, OKF, Lebenslauf- und LinkedIn-Optimierung sowie zahlreiche Referenzdateien, Checklisten und YAML/JSON/Markdown-Templates. Einführung einer vollständigen OpenWiki-Dokumentation mit Architektur-, Domain- und Workflow-Beschreibungen, zentralem Index und automatisierten Updates. Modularer Aufbau, restriktive Lizenzen und umfassende Qualitäts- und Evaluationsmechanismen für alle neuen Inhalte.

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+# Language and Grammar Patterns (English)
+
+Patterns that betray AI-generated text at the level of word choice, grammatical constructions, and sentence structure. Based on Wikipedia's Signs of AI Writing + tropes.fyi + blader/humanizer's 29-pattern set + brandonwise/humanizer's statistical model.
+
+---
+
+### 1. AI Vocabulary (The Slop Dictionary)
+
+**Tier 1 - Zero Tolerance (cut on sight):**
+
+| Word/Phrase | Why it's a tell | Human alternative |
+|---|---|---|
+| delve | No one says this in conversation | explore, dig into, look at |
+| tapestry | Always used as "rich tapestry of..." | (cut entirely - always filler) |
+| landscape (figurative) | "The AI landscape" | the AI space, AI right now |
+| testament to | "It's a testament to..." | shows that, proves |
+| serves as a reminder | Always preamble to nothing | (cut - just state the thing) |
+| it's worth noting | Meta-commentary, not content | (cut - the note IS the content) |
+| it bears mentioning | Same as above | (cut) |
+| the ever-evolving landscape | Double slop | (cut entirely) |
+| navigate (complexities) | "Navigate the challenges of" | deal with, handle, figure out |
+| spearhead | "Spearheading the initiative" | lead, run, start |
+| multifaceted | "This multifaceted problem" | complex, messy, complicated |
+| pivotal | "A pivotal moment" | important, key, big |
+| paramount | "Of paramount importance" | essential, critical |
+| underscores | "This underscores the need" | shows, highlights |
+| underpin | "Principles that underpin" | behind, supporting |
+| in the realm of | "In the realm of AI" | in AI |
+| shed light on | "Shedding light on this issue" | explain, clarify, show |
+| this highlights | Meta-commentary | (cut - the highlight IS the sentence) |
+
+**Tier 2 - High Suspicion (replace when clustered, OK once per 1000 words):**
+
+`crucial, vital, comprehensive, robust, leverage, foster, facilitate, embark, harnessing, utilize, endeavor, moreover, furthermore, additionally, subsequently, nonetheless, overarching, intricate, nuanced, holistic, synergy, paradigm, catalyst, orchestrate, seamless, ecosystem (abstract), journey (figurative), unlock (figurative), empower, elevate`
+
+**Tier 3 - Context-Dependent (flag if >2 per 500 words):**
+
+`significant, enhance, innovative, dynamic, diverse, inclusive, sustainable, transformative, streamline, optimize, cutting-edge, state-of-the-art, game-changer, disruptive, scalable, impactful, actionable, meaningful, compelling, groundbreaking`
+
+**Detection rule:**
+- 1 Tier-1 word = flag the sentence
+- 3+ Tier-2 words in one paragraph = flag the paragraph
+- 5+ Tier-3 words in one page = flag the text
+- Any combination of 2+ Tier-1 words in 500 words = near-certain AI
+
+---
+
+### 2. Copula Avoidance
+
+**Trigger patterns:** constitutes, represents, serves as, functions as, operates as, positions itself as, stands as, emerges as, figures as
+
+**Problem:** AI avoids "is" and "has" as if they were forbidden words. Replaces them with elaborate constructions no human would use in natural writing.
+
+**Before (AI):**
+> Stripe constitutes the leading payments infrastructure for the internet. The platform serves as a comprehensive solution for businesses and positions itself as the de facto standard for online transactions.
+
+**After (human):**
+> Stripe is the biggest payments company online. Their API is what most startups use to take money.
+
+**Rule:** If "is" or "has" would work, use it. Save elaborate verbs for when you need precise meaning, not sophistication theater.
+
+---
+
+### 3. Negative Parallelisms
+
+**Trigger patterns:** not merely X, but Y; it's not just about X, it's about Y; more than X, it's Y; goes far beyond X; transcends the simple X; not simply X, it's fundamentally Y
+
+**Problem:** Formulaic construction that artificially inflates importance. Creates a false dichotomy where the writer pretends to reject something then embraces something bigger - but both parts say the same thing.
+
+**Before (AI):**
+> Product management is not merely about writing user stories. It goes far beyond simply shipping features - it's fundamentally about solving real problems. The PM transcends the role of ticket writer; they are, above all, a translator between business and technology.
+
+**After (human):**
+> Good PMs solve problems. Bad PMs write tickets. The difference isn't philosophical - it's practical. Look at someone's backlog and you'll know in 5 minutes.
+
+---
+
+### 4. Tricolon Abuse (Rule of Three)
+
+**Trigger patterns:** clarity, concision, and coherence; innovation, technology, and transformation; plan, execute, and measure; any rhythmic triad with "and" before the third item; three adjectives in sequence; three abstract nouns grouped
+
+**Problem:** AI groups ideas in threes because tricolon is rhetorically satisfying - but when it appears in every paragraph, it becomes a tic. Human text groups in 2, in 4, in 1. Rarely in 3 repeatedly.
+
+**Before (AI):**
+> The platform delivers speed, reliability, and scalability. Teams need clarity, collaboration, and consistency. Our approach combines innovation, expertise, and dedication.
+
+**After (human):**
+> It's fast. Reliable enough that we stopped worrying about downtime. And it scales - we went from 10k to 400k requests/day without changing anything.
+
+**Detection rule:** If a text has 3+ tricolons per page, it's almost certainly AI-generated. Humans occasionally use rule-of-three for rhetorical effect. AI uses it as a structural crutch.
+
+---
+
+### 5. Weasel Qualifiers
+
+**Trigger patterns:** it could be argued that, one might suggest, there are those who believe, it has been said that, some would argue, many experts believe, it is generally accepted
+
+**Problem:** AI uses qualifiers to avoid committing to claims. The result reads like a Wikipedia article written by someone afraid of being corrected. Humans either commit to a claim or cite a specific source.
+
+**Before (AI):**
+> It could be argued that large language models represent a significant advancement. Many experts believe this technology has the potential to transform various industries, though some would argue the risks are considerable.
+
+**After (human):**
+> LLMs are a big deal. They'll change how most knowledge work gets done - I genuinely believe that. But Hinton is right that we don't understand alignment well enough to be comfortable.
+
+---
+
+### 6. Nominalization Disease
+
+**Trigger patterns:** the implementation of, the utilization of, the facilitation of, the optimization of, the enhancement of, the establishment of, provides a demonstration of, performs an analysis of
+
+**Problem:** AI converts verbs into nouns, making sentences longer, vaguer, and harder to parse. "We analyzed" becomes "we performed an analysis of". This is the passive-aggressive cousin of passive voice.
+
+**Before (AI):**
+> The implementation of the new system resulted in the enhancement of performance metrics and the facilitation of improved collaboration across teams.
+
+**After (human):**
+> We implemented the new system. Performance improved. Teams started collaborating more.
+
+**Rule:** If a noun ending in -tion/-ment/-ance has a simpler verb form, use the verb.