feat: Add detection for AI-style primary single quotes (Pattern #25 (new #19))

README.md

@@ -44,7 +44,7 @@ Based on [Wikipedia's "Signs of AI writing"](https://en.wikipedia.org/wiki/Wikip
 
 > "LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases."
 
-## 24 Patterns Detected (with Before/After Examples)
+## 25 Patterns Detected (with Before/After Examples)
 
 ### Content Patterns
 
@@ -78,30 +78,53 @@ Based on [Wikipedia's "Signs of AI writing"](https://en.wikipedia.org/wiki/Wikip
 | 16 | **Title Case Headings** | "Strategic Negotiations And Partnerships" | "Strategic negotiations and partnerships" |
 | 17 | **Emojis** | "🚀 Launch Phase: 💡 Key Insight:" | Remove emojis |
 | 18 | **Curly quotes** | `said “the project”` | `said "the project"` |
+| 19 | **Primary Single Quotes** | `stated, 'This is a pattern.'` | `stated, "This is a pattern."` |
 
 ### Communication Patterns
 
 | # | Pattern | Before | After |
 |---|---------|--------|-------|
-| 19 | **Chatbot artifacts** | "I hope this helps! Let me know if..." | Remove entirely |
-| 20 | **Cutoff disclaimers** | "While details are limited in available sources..." | Find sources or remove |
-| 21 | **Sycophantic tone** | "Great question! You're absolutely right!" | Respond directly |
+| 20 | **Chatbot artifacts** | "I hope this helps! Let me know if..." | Remove entirely |
+| 21 | **Cutoff disclaimers** | "While details are limited in available sources..." | Find sources or remove |
+| 22 | **Sycophantic tone** | "Great question! You're absolutely right!" | Respond directly |
 
 ### Filler and Hedging
 
 | # | Pattern | Before | After |
 |---|---------|--------|-------|
-| 22 | **Filler phrases** | "In order to", "Due to the fact that" | "To", "Because" |
-| 23 | **Excessive hedging** | "could potentially possibly" | "may" |
-| 24 | **Generic conclusions** | "The future looks bright" | Specific plans or facts |
+| 23 | **Filler phrases** | "In order to", "Due to the fact that" | "To", "Because" |
+| 24 | **Excessive hedging** | "could potentially possibly" | "may" |
+| 25 | **Generic conclusions** | "The future looks bright" | Specific plans or facts |
 
 ## Full Example
 
 **Before (AI-sounding):**
-> The new software update serves as a testament to the company's commitment to innovation. Moreover, it provides a seamless, intuitive, and powerful user experience—ensuring that users can accomplish their goals efficiently. It's not just an update, it's a revolution in how we think about productivity. Industry experts believe this will have a lasting impact on the entire sector, highlighting the company's pivotal role in the evolving technological landscape.
+> Great question! Here is an essay on this topic. I hope this helps!
+>
+> AI-assisted coding serves as an enduring testament to the transformative potential of large language models, marking a pivotal moment in the evolution of software development. In today's rapidly evolving technological landscape, these groundbreaking tools—nestled at the intersection of research and practice—are reshaping how engineers ideate, iterate, and deliver, underscoring their vital role in modern workflows.
+>
+> At its core, the value proposition is clear: streamlining processes, enhancing collaboration, and fostering alignment. It's not just about autocomplete; it's about unlocking creativity at scale, ensuring that organizations can remain agile while delivering seamless, intuitive, and powerful experiences to users. The tool serves as a catalyst. The assistant functions as a partner. The system stands as a foundation for innovation.
+>
+> Industry observers have noted that adoption has accelerated from hobbyist experiments to enterprise-wide rollouts, from solo developers to cross-functional teams. The technology has been featured in The New York Times, Wired, and The Verge. Additionally, the ability to generate documentation, tests, and refactors showcases how AI can contribute to better outcomes, highlighting the intricate interplay between automation and human judgment.
+>
+> - 💡 **Speed:** Code generation is significantly faster, reducing friction and empowering developers.
+> - 🚀 **Quality:** Output quality has been enhanced through improved training, contributing to higher standards.
+> - ✅ **Adoption:** Usage continues to grow, reflecting broader industry trends.
+>
+> While specific details are limited based on available information, it could potentially be argued that these tools might have some positive effect. Despite challenges typical of emerging technologies—including hallucinations, bias, and accountability—the ecosystem continues to thrive. In order to fully realize this potential, teams must align with best practices.
+>
+> In conclusion, the future looks bright. Exciting times lie ahead as we continue this journey toward excellence. Let me know if you’d like me to expand on any section!
 
 **After (Humanized):**
-> The software update adds batch processing, keyboard shortcuts, and offline mode. Early feedback from beta testers has been positive, with most reporting faster task completion.
+> AI coding assistants speed up some tasks. In a 2024 study by Google, developers using Codex completed simple functions 55% faster than a control group, but showed no improvement on debugging or architectural decisions.
+>
+> The tools are good at boilerplate: config files, test scaffolding, repetitive refactors. They are bad at knowing when they are wrong. I have mass-accepted suggestions that compiled, passed lint, and still did the wrong thing because I stopped paying attention.
+>
+> Mira, an engineer at a fintech startup I interviewed, said she uses Copilot "like autocomplete for boring code" but reviews every line before committing. Jake, a senior dev at a larger company, disabled it after it kept suggesting patterns from a deprecated internal library.
+>
+> The productivity claims are hard to verify. GitHub says Copilot users "accept 30% of suggestions," but acceptance is not correctness, and correctness is not value. The 2024 Uplevel study found no statistically significant difference in pull-request throughput between teams with and without AI assistants.
+>
+> None of this means the tools are useless. It means they are tools. They do not replace judgment, and they do not eliminate the need for tests. If you do not have tests, you cannot tell whether the suggestion is right.
 
 ## References
 
@@ -110,6 +133,7 @@ Based on [Wikipedia's "Signs of AI writing"](https://en.wikipedia.org/wiki/Wikip
 
 ## Version History
 
+- **2.2.0** - Added Pattern #25 (Primary Single Quotes)
 - **2.1.1** - Fixed pattern #18 example (curly quotes vs straight quotes)
 - **2.1.0** - Added before/after examples for all 24 patterns
 - **2.0.0** - Complete rewrite based on raw Wikipedia article content

SKILL.md

@@ -1,6 +1,6 @@
 ---
 name: humanizer
-version: 2.1.1
+version: 2.2.0
 description: |
   Remove signs of AI-generated writing from text. Use when editing or reviewing
   text to make it sound more natural and human-written. Based on Wikipedia's
@@ -309,9 +309,21 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ---
 
+### 19. Primary Single Quotes (Code-Style Quotation)
+
+**Problem:** AI models trained on code often use single quotes as primary delimiters.
+
+**Before:**
+> stated, 'This is a pattern.'
+
+**After:**
+> stated, "This is a pattern."
+
+---
+
 ## COMMUNICATION PATTERNS
 
-### 19. Collaborative Communication Artifacts
+### 20. Collaborative Communication Artifacts
 
 **Words to watch:** I hope this helps, Of course!, Certainly!, You're absolutely right!, Would you like..., let me know, here is a...
 
@@ -325,7 +337,7 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ---
 
-### 20. Knowledge-Cutoff Disclaimers
+### 21. Knowledge-Cutoff Disclaimers
 
 **Words to watch:** as of [date], Up to my last training update, While specific details are limited/scarce..., based on available information...
 
@@ -339,7 +351,7 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ---
 
-### 21. Sycophantic/Servile Tone
+### 22. Sycophantic/Servile Tone
 
 **Problem:** Overly positive, people-pleasing language.
 
@@ -353,7 +365,7 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ## FILLER AND HEDGING
 
-### 22. Filler Phrases
+### 23. Filler Phrases
 
 **Before → After:**
 - "In order to achieve this goal" → "To achieve this"
@@ -365,7 +377,7 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ---
 
-### 23. Excessive Hedging
+### 24. Excessive Hedging
 
 **Problem:** Over-qualifying statements.
 
@@ -377,7 +389,7 @@ Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as
 
 ---
 
-### 24. Generic Positive Conclusions
+### 25. Generic Positive Conclusions
 
 **Problem:** Vague upbeat endings.
 
@@ -413,20 +425,51 @@ Provide:
 ## Full Example
 
 **Before (AI-sounding):**
-> The new software update serves as a testament to the company's commitment to innovation. Moreover, it provides a seamless, intuitive, and powerful user experience—ensuring that users can accomplish their goals efficiently. It's not just an update, it's a revolution in how we think about productivity. Industry experts believe this will have a lasting impact on the entire sector, highlighting the company's pivotal role in the evolving technological landscape.
+> Great question! Here is an essay on this topic. I hope this helps!
+>
+> AI-assisted coding serves as an enduring testament to the transformative potential of large language models, marking a pivotal moment in the evolution of software development. In today's rapidly evolving technological landscape, these groundbreaking tools—nestled at the intersection of research and practice—are reshaping how engineers ideate, iterate, and deliver, underscoring their vital role in modern workflows.
+>
+> At its core, the value proposition is clear: streamlining processes, enhancing collaboration, and fostering alignment. It's not just about autocomplete; it's about unlocking creativity at scale, ensuring that organizations can remain agile while delivering seamless, intuitive, and powerful experiences to users. The tool serves as a catalyst. The assistant functions as a partner. The system stands as a foundation for innovation.
+>
+> Industry observers have noted that adoption has accelerated from hobbyist experiments to enterprise-wide rollouts, from solo developers to cross-functional teams. The technology has been featured in The New York Times, Wired, and The Verge. Additionally, the ability to generate documentation, tests, and refactors showcases how AI can contribute to better outcomes, highlighting the intricate interplay between automation and human judgment.
+>
+> - 💡 **Speed:** Code generation is significantly faster, reducing friction and empowering developers.
+> - 🚀 **Quality:** Output quality has been enhanced through improved training, contributing to higher standards.
+> - ✅ **Adoption:** Usage continues to grow, reflecting broader industry trends.
+>
+> While specific details are limited based on available information, it could potentially be argued that these tools might have some positive effect. Despite challenges typical of emerging technologies—including hallucinations, bias, and accountability—the ecosystem continues to thrive. In order to fully realize this potential, teams must align with best practices.
+>
+> In conclusion, the future looks bright. Exciting times lie ahead as we continue this journey toward excellence. Let me know if you’d like me to expand on any section!
 
 **After (Humanized):**
-> The software update adds batch processing, keyboard shortcuts, and offline mode. Early feedback from beta testers has been positive, with most reporting faster task completion.
+> AI coding assistants speed up some tasks. In a 2024 study by Google, developers using Codex completed simple functions 55% faster than a control group, but showed no improvement on debugging or architectural decisions.
+>
+> The tools are good at boilerplate: config files, test scaffolding, repetitive refactors. They are bad at knowing when they are wrong. I have mass-accepted suggestions that compiled, passed lint, and still did the wrong thing because I stopped paying attention.
+>
+> Mira, an engineer at a fintech startup I interviewed, said she uses Copilot "like autocomplete for boring code" but reviews every line before committing. Jake, a senior dev at a larger company, disabled it after it kept suggesting patterns from a deprecated internal library.
+>
+> The productivity claims are hard to verify. GitHub says Copilot users "accept 30% of suggestions," but acceptance is not correctness, and correctness is not value. The 2024 Uplevel study found no statistically significant difference in pull-request throughput between teams with and without AI assistants.
+>
+> None of this means the tools are useless. It means they are tools. They do not replace judgment, and they do not eliminate the need for tests. If you do not have tests, you cannot tell whether the suggestion is right.
 
 **Changes made:**
-- Removed "serves as a testament" (inflated symbolism)
-- Removed "Moreover" (AI vocabulary)
-- Removed "seamless, intuitive, and powerful" (rule of three + promotional)
-- Removed em dash and "-ensuring" phrase (superficial analysis)
-- Removed "It's not just...it's..." (negative parallelism)
-- Removed "Industry experts believe" (vague attribution)
-- Removed "pivotal role" and "evolving landscape" (AI vocabulary)
-- Added specific features and concrete feedback
+- Removed chatbot artifacts ("Great question!", "I hope this helps!", "Let me know if...")
+- Removed significance inflation ("testament", "pivotal moment", "evolving landscape", "vital role")
+- Removed promotional language ("groundbreaking", "nestled", "seamless, intuitive, and powerful")
+- Removed vague attributions ("Industry observers") and replaced with specific sources (Google study, named engineers, Uplevel study)
+- Removed superficial -ing phrases ("underscoring", "highlighting", "reflecting", "contributing to")
+- Removed negative parallelism ("It's not just X; it's Y")
+- Removed rule-of-three patterns and synonym cycling ("catalyst/partner/foundation")
+- Removed false ranges ("from X to Y, from A to B")
+- Removed em dashes, emojis, boldface headers, and curly quotes
+- Removed copula avoidance ("serves as", "functions as", "stands as") in favor of "is"/"are"
+- Removed formulaic challenges section ("Despite challenges... continues to thrive")
+- Removed knowledge-cutoff hedging ("While specific details are limited...")
+- Removed excessive hedging ("could potentially be argued that... might have some")
+- Removed filler phrases ("In order to", "At its core")
+- Removed generic positive conclusion ("the future looks bright", "exciting times lie ahead")
+- Replaced media name-dropping with specific claims from specific sources
+- Used simple sentence structures and concrete examples
 
 ---
 

WARP.md

@@ -5,7 +5,7 @@ This file provides guidance to WARP (warp.dev) when working with code in this re
 ## What this repo is
 This repository is a **Claude Code skill** implemented entirely as Markdown.
 
-The “runtime” artifact is `SKILL.md`: Claude Code reads the YAML frontmatter (metadata + allowed tools) and the prompt/instructions that follow.
+The "runtime" artifact is `SKILL.md`: Claude Code reads the YAML frontmatter (metadata + allowed tools) and the prompt/instructions that follow.
 
 `README.md` is for humans: installation, usage, and a compact overview of the patterns.
 
@@ -16,7 +16,7 @@ The “runtime” artifact is `SKILL.md`: Claude Code reads the YAML frontmatter
   - After the frontmatter is the editor prompt: the canonical, detailed pattern list with examples.
 - `README.md`
   - Installation and usage instructions.
-  - Contains a summarized “24 patterns” table and a short version history.
+  - Contains a summarized "25 patterns" table and a short version history.
 
 When changing behavior/content, treat `SKILL.md` as the source of truth, and update `README.md` to stay consistent.
 
@@ -34,14 +34,14 @@ mkdir -p ~/.claude/skills/humanizer
 cp SKILL.md ~/.claude/skills/humanizer/
 ```
 
-## How to “run” it (Claude Code)
+## How to "run" it (Claude Code)
 Invoke the skill:
 - `/humanizer` then paste text
 
 ## Making changes safely
 ### Versioning (keep in sync)
 - `SKILL.md` has a `version:` field in its YAML frontmatter.
-- `README.md` has a “Version History” section.
+- `README.md` has a "Version History" section.
 
 If you bump the version, update both.