By Scratchydisk
Personal Claude Code skills library: workflow orchestration (devil's-advocate loops), behavioural guidelines (karpathy-guidelines), and writing-quality checks (anti-ai-tells).
Strip the AI-chatbot fingerprint out of written content. Use whenever drafting, editing, or reviewing prose that needs to read as human-written — articles, blog posts, essays, reports, Wikipedia edits, marketing copy, emails, fiction, anything where "this was clearly written by ChatGPT" would be a problem. Also use as a self-review pass after generating any long-form text, even if the user didn't explicitly ask for it to sound human. Based on Wikipedia's "Signs of AI writing" field guide (WP:AISIGNS), the most comprehensive empirical catalog of LLM writing tells in existence.
Iterates devil's-advocate review on a plan or spec until a round finds no real bugs. Each round: surface concerns, apply fixes inline, commit, repeat. Min 2 rounds, max 4. Stops when only nits/cosmetic issues remain. Use when refining a written artifact before execution — not for one-shot review (use /devils-advocate for that).
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
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npx claudepluginhub scratchydisk/claude-skills --plugin scratchydisk-skillsComprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Behavioral guidelines to reduce common LLM coding mistakes, derived from Andrej Karpathy's observations on LLM coding pitfalls
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.