emblem-market-research은(는) 무엇을 하나요?
EmblemAI를 통한 암호화폐 시장 인텔리전스. CoinGecko, CoinGlass, Birdeye, Nansen의 트렌딩 토큰, 온체인 분석, 파생상품 데이터, 스마트 머니 추적을 제공합니다. 사용자가 시장 데이터, 트렌딩 토큰, 파생상품 분석, 또는 온체인 인텔리전스를 원할 때 사용하세요.
EmblemAI를 통한 암호화폐 시장 인텔리전스. CoinGecko, CoinGlass, Birdeye, Nansen의 트렌딩 토큰, 온체인 분석, 파생상품 데이터, 스마트 머니 추적을 제공합니다. 사용자가 시장 데이터, 트렌딩 토큰, 파생상품 분석, 또는 온체인 인텔리전스를 원할 때 사용하세요.
이 스킬은 EmblemAI 플랫폼을 기반으로 암호화폐 시장에 대한 포괄적인 인텔리전스를 제공합니다. CoinGecko, CoinGlass, Birdeye, Nansen과 같은 주요 데이터 제공업체에서 트렌딩 토큰, 온체인 분석, 파생상품 데이터, 스마트 머니 추적 정보를 수집합니다. 개발자나 AI 에이전트 사용자가 시장 동향을 파악하고, 특정 토큰의 온체인 활동을 분석하며, 파생상품 시장의 변동성을 평가하고, 고래 또는 기관 투자자의 움직임을 추적해야 할 때 유용합니다. 주요 사용 사례로는 실시간 가격 조회, 거래량 분석, 파생상품 미결제약정 확인, 스마트 머니 흐름 추적 등이 있으며, Claude Code, Cursor, Codex 등 다양한 AI 에이전트 플랫폼에서 사용할 수 있도록 설계되었습니다.
npx skills add https://github.com/emblemcompany/agent-skills/tree/main/skills/emblem-market-researchInstalled? Explore more 연구 & 데이터 분석 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
EmblemAI를 통한 암호화폐 시장 인텔리전스. CoinGecko, CoinGlass, Birdeye, Nansen의 트렌딩 토큰, 온체인 분석, 파생상품 데이터, 스마트 머니 추적을 제공합니다. 사용자가 시장 데이터, 트렌딩 토큰, 파생상품 분석, 또는 온체인 인텔리전스를 원할 때 사용하세요.
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.
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.