emblem-memecoin-scout 是做什麼的？
透過 EmblemAI 進行迷因幣發現與風險評估。支援 Solana、Base 和 Hedera 上的熱門迷因幣，Pump.fun 和 LaunchLab 新代幣提醒、Clanker 發現、Rug Pull 偵測、持有者分析及聰明錢追蹤。當使用者想尋找新的迷因幣、檢查代幣是否為 Rug Pull，或搜尋趨勢性低市值代幣時，請使用此技能。
透過 EmblemAI 進行迷因幣發現與風險評估。支援 Solana、Base 和 Hedera 上的熱門迷因幣，Pump.fun 和 LaunchLab 新代幣提醒、Clanker 發現、Rug Pull 偵測、持有者分析及聰明錢追蹤。
Emblem Memecoin Scout 是一個專業的迷因幣探索與風險評估技能，由 EmblemAI 驅動。它能幫助用戶在 Solana、Base 和 Hedera 等區塊鏈上發現新興的迷因幣，並提供即時警報（如 Pump.fun 和 LaunchLab 的新代幣上線通知、Clanker 發現）。此外，該技能內建 Rug Pull 偵測機制，透過持有者分析與聰明錢追蹤，協助判斷代幣是否為騙局或具備投資潛力。支援的平台包括主流鏈與迷因幣發射台，適合需要尋找低市值迷因幣、檢查代幣安全性或追蹤市場趨勢的開發者與交易者。其工作原理是整合區塊鏈資料與 EmblemAI 的模型分析，輸出風險評分與熱門度指標。
npx skills add https://github.com/emblemcompany/agent-skills/tree/main/skills/emblem-memecoin-scoutInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
透過 EmblemAI 進行迷因幣發現與風險評估。支援 Solana、Base 和 Hedera 上的熱門迷因幣，Pump.fun 和 LaunchLab 新代幣提醒、Clanker 發現、Rug Pull 偵測、持有者分析及聰明錢追蹤。當使用者想尋找新的迷因幣、檢查代幣是否為 Rug Pull，或搜尋趨勢性低市值代幣時，請使用此技能。
This repo contains 8 individual skills — each has its own dedicated page.
One-shot user management for apps, multi-chain wallet authentication, an AI-powered assistant, and AI app introspection. Use when the user wants to let website users sign in with wallets, email/password, or social login and give each user a wallet-enabled account, then embed EmblemAI chat surfaces, connect plugins, or add Reflexive observability. Provides React components, TypeScript SDKs, session-based authentication, and pointers to the React and agent-wallet skills for specialized workflows.
Connect to EmblemVault and manage wallet-aware workflows via EmblemAI with review-first, operator-controlled actions. Supports Solana, Ethereum, Base, BSC, Polygon, Hedera, and Bitcoin. Also use when the user needs Emblem's auth model explained: one browser auth flow can log a user in with wallets, email/password, or social sign-in, while agent mode can auto-provision a profile-scoped wallet with no manual setup.
Curated prompt and usage examples for research, portfolio review, quote requests, approval-gated drafts, NFT discovery, prediction-market analysis, and assistant workflows. Emphasis is review-first, trust-boundary-aware use of external data, and explicit confirmation before any value-moving action. Use when the user wants example prompts, phrasing guidance, or sample requests for end-user EmblemAI tasks.
React integration skill for EmblemAI's one-shot user management. Use when the user wants to add website authentication plus wallet-enabled users to a React app with EmblemAuthProvider, ConnectButton, social/email/wallet login, chat components, React auth hooks, React composition patterns, or Migrate.fun React hooks.
DeFi yield research and liquid staking via EmblemAI. Discover yield opportunities, compare protocols, check DeFi positions with Nansen, and enter liquid staking via token swaps. Use when the user wants to research yields, find staking options, or review DeFi positions.
Crypto market intelligence via EmblemAI. Trending tokens, on-chain analytics, derivatives data, and smart money tracking from CoinGecko, CoinGlass, Birdeye, and Nansen. Use when the user wants market data, trending tokens, derivatives analytics, or on-chain intelligence.
Track crypto portfolio across 7 blockchains via EmblemAI. Aggregated balances with USD values, conditional trade P&L, and DeFi position tracking via Nansen. Use when the user wants to check their portfolio, see balances across chains, or review trade positions.
Execute token swaps across 6 blockchains via EmblemAI. Automatic route optimization and cross-chain bridging via ChangeNow. Use when the user wants to swap tokens, exchange crypto, convert between currencies, or bridge assets cross-chain.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.