emblem-defi-yield は何をしますか？
EmblemAIによるDeFi利回り調査とリキッドステーキング。利回り機会の発見、プロトコル比較、Nansenを使ったDeFiポジションの確認、トークンスワップによるリキッドステーキングの開始を行います。ユーザーが利回りを調査したい、ステーキングオプションを探したい、またはDeFiポジションを確認したい場合に使用します。
EmblemAIによるDeFi利回り調査とリキッドステーキング。利回り機会の発見、プロトコル比較、Nansenを使ったDeFiポジションの確認、トークンスワップによるリキッドステーキングの開始を行います。ユーザーが利回りを調査したい、ステーキングオプションを探したい、またはDeFiポジションを確認したい場合に使用します。
このスキルは、EmblemAIプラットフォームを活用してDeFiの利回り調査とリキッドステーキングを実行するためのツールです。ユーザーは、複数のプロトコルにまたがる利回り機会を発見・比較し、Nansenデータを用いて自身のDeFiポジションを確認できます。また、トークンスワップを通じてリキッドステーキングに参加することも可能です。主にClaude Codeや類似のAIエージェント上で動作し、DeFiに関する情報収集とアクションを効率的に行えるように設計されています。このスキルの有用性は、ステーキングオプションの調査からポジション管理までを一貫してサポートする点にあります。
npx skills add https://github.com/emblemcompany/agent-skills/tree/main/skills/emblem-defi-yieldInstalled? Explore more 研究＆データ分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
EmblemAIによるDeFi利回り調査とリキッドステーキング。利回り機会の発見、プロトコル比較、Nansenを使ったDeFiポジションの確認、トークンスワップによるリキッドステーキングの開始を行います。ユーザーが利回りを調査したい、ステーキングオプションを探したい、またはDeFiポジションを確認したい場合に使用します。
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.
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.
Memecoin discovery and risk assessment via EmblemAI. Trending memecoins on Solana, Base, and Hedera. Pump.fun and LaunchLab new token alerts, Clanker discovery, rug-pull detection, holder analysis, and smart money tracking. Use when the user wants to find new memecoins, check if a token is a rug pull, or scout trending low-cap tokens.
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.