Research top-performing Xiaohongshu (小红书 / XHS) image posts, analyze titles/content/comments for patterns and emotional resonance, enrich background via Firecrawl MCP, then write and publish an XHS note via Xiaohongshu MCP. Enforce hard limits: title <= 20 characters, body <= 1000 characters. Use when the user asks for 小红书笔记/种草文案/爆款标题/发布到小红书.
npx skills add https://github.com/adjfks/corner-skills/tree/main/skills/write-xiaohongshuResearch top-performing Xiaohongshu (小红书 / XHS) image posts, analyze titles/content/comments for patterns and emotional resonance, enrich background via Firecrawl MCP, then write and publish an XHS note via Xiaohongshu MCP. Enforce hard limits: title <= 20 characters, body <= 1000 characters. Use when the user asks for 小红书笔记/种草文案/爆款标题/发布到小红书.
Manage health data with an offline-first AI assistant using Gemma 4B on React Native for symptom triage, drug lookup, and private multi-agent health insights.
AI-powered OSINT agent with interactive REPL, MCP server, and CLI. 9 tools. Works with Claude, GPT-4, or local models. For authorized security research only.
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
Comprehensive personal finance management system for analyzing transaction data, generating insights, creating visualizations, and providing actionable financial recommendations. Use when users need to analyze spending patterns, track budgets, visualize financial data, extract transactions from PDFs, calculate savings rates, identify spending trends, generate financial reports, or receive personalized budget recommendations. Triggers include requests like "analyze my finances", "track my spending", "create a financial report", "extract transactions from PDF", "visualize my budget", "where is my money going", "financial insights", "spending breakdown", or any finance-related analysis tasks.
Easy-to-use, high-efficiency threat modeling agent skills.
Optimize LLM system quality by using this outer-loop meta-harness to automate the search, evaluation, and mutation of agent benchmarking code.