n8n-io/n8n-hacker-news-mcp
Complete MCP server exposing all Hacker News Tool operations. Zero config, pre-built workflows
Complete MCP server exposing all Hacker News Tool operations. Zero config, pre-built workflows
npx skills add n8n-io/n8n-hacker-news-mcpComplete MCP server exposing all Hacker News Tool operations. Zero config, pre-built workflows
Apply Warren Buffett’s investment framework to your financial analysis using this collection of Claude Code skills.
AI-agent workflow governance kit with multi-agent routing, runtime safety gates, semantic skill evaluation, evidence ledger, and readiness checks.
The Anti-Hallucination data layer for B2B Sourcing. Deep-verified global supply chain entities designed for RAG and LLM instruction tuning.
Use when the user wants to publish new content to Binance Square — short text, multi-image posts (up to 4), long-form articles with an optional cover, or videos with an auto-generated cover frame. Trigger on direct phrasings like "post to Square", "publish to Binance Square", "发广场", "发布到广场", and on near-miss intents where the user clearly wants to share or publish content on Square even without naming the skill: "share this analysis on Square", "把这篇文章发出去", "发个动态", "把这个视频上传到广场", "publish my chart to Square as an article". Also use when the user provides media (images, video) plus a caption and asks to push it to Square, or asks to turn a draft into a Square article. Do not use for reading, searching, commenting, liking, editing, deleting, scheduling, or managing existing Square posts — this skill only creates new posts.
Load automatically when planning, researching, or implementing Medusa storefront features (calling custom API routes, SDK integration, React Query patterns, data fetching). REQUIRED for all storefront development in ALL modes (planning, implementation, exploration). Contains SDK usage patterns, frontend integration, and critical rules for calling Medusa APIs.
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.