emblem-market-research 是做什么的？
通过 EmblemAI 获取加密货币市场情报。包括热门代币、链上分析、衍生品数据和聪明钱追踪，数据源涵盖 CoinGecko、CoinGlass、Birdeye 和 Nansen。当用户需要市场数据、热门代币、衍生品分析或链上情报时使用。
通过 EmblemAI 获取加密货币市场情报。包括热门代币、链上分析、衍生品数据和聪明钱追踪，数据源涵盖 CoinGecko、CoinGlass、Birdeye 和 Nansen。当用户需要市场数据、热门代币、衍生品分析或链上情报时使用。
该技能通过 EmblemAI 平台，为 AI 代理提供全面的加密货币市场情报能力。它集成了多个顶级数据源（CoinGecko、CoinGlass、Birdeye、Nansen），能够获取热门代币、链上分析、衍生品数据和聪明钱追踪等关键信息。开发者可以利用此技能快速回答用户关于市场趋势、代币表现、衍生品合约及大额资金流向的查询。支持在 Claude Code、Cursor、Codex 等 AI 代理环境中使用，通过自然语言指令即可获取实时或历史数据。技能内部封装了与各数据源 API 的交互逻辑，并提供了标准化的输出格式，使得 AI 代理能够高效地解析和呈现复杂的市场信息。
npx skills add https://github.com/emblemcompany/agent-skills/tree/main/skills/emblem-market-researchInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
通过 EmblemAI 获取加密货币市场情报。包括热门代币、链上分析、衍生品数据和聪明钱追踪，数据源涵盖 CoinGecko、CoinGlass、Birdeye 和 Nansen。当用户需要市场数据、热门代币、衍生品分析或链上情报时使用。
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.