Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Current Ethereum gas prices and real transaction costs in 2026 — counters the misconception that Ethereum is expensive. Covers mainnet vs L2 comparison, why gas dropped 95%+, and live gas trackers.
Urizen — an AI equity-research desk + the first autonomous fund on Robinhood Chain (4663), as an agent skill. Real charts & technicals for any tokenized US stock, SEC fundamentals + filings + insider activity, Wall Street analyst consensus, financial news, the macro calendar (Fed/CPI/jobs), live prediction-market odds, and on-chain price — plus the fund's live strategies, book, execution tape, and one-token exposure via $URI. Public, key-less, CORS-open REST on chain 4663. Triggers on: "urizen", "research a stock", "tokenized stock", "SEC fundamentals", "analyst rating", "economic calendar", "prediction market odds", "copy trade the fund", "urizen book", "buy $URI".
Why build on Ethereum — the AI agent angle with ERC-8004 identity, x402 payments, composability, and permissionless deployment. Corrects common misconceptions about gas costs, terminology, and network status.
Explore unfamiliar APIs, libraries, or implementation behavior with minimal reproducible examples and documented findings. Use when implementation details are unclear and can be resolved by reading docs, inspecting code, and running focused experiments.
Perform structured research and turn findings into an implementation plan.
Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, LinkedIn, and Amazon. Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries.
Coordinate raw analysis and publish a normalized research entry into chan.dev's `src/content/research/`. Use when research should become a durable chan.dev report.
Search the Genie Sim asset library by natural-language keyword via the generator's `search_assets` MCP tool (RAG over ASSETS_INDEX), and look up asset interaction metadata via `get_interactions`. Trigger: When the user asks to "搜索资产", "find an asset", "查一下有没有...的模型", "search the asset library", "what assets match <description>", "look up asset_id X", or wants to know which assets exist before generating a scene.
Gene set enrichment analysis with correct geneset format handling. Critical guidance for loading pathway databases and running enrichment in OmicVerse.