analyze-crypto

Analyze Crypto — One-click comprehensive cryptocurrency analysis

Enter a token name or symbol, automatically collect data across five dimensions in parallel, and output a standard report after comprehensive analysis.

When to Use

Triggered when the user requests the following operations:

"Analyze BTC" / "Analyze Ethereum" / "Analyze SOL"
"analyze BTC" / "analyze Ethereum"
"How is Bitcoin doing" / "Why has ETH been rising/falling recently"
"Help me look at SOL" / "Is DOGE worth buying"

Phase 0: Parse input

Based on the user input, identify the following information:

Token name mapping(common token Chinese-English correspondence)
- Bitcoin/Bitcoin → BTC
- Ethereum/Ethereum → ETH
- Solana/Solana → SOL
- Ripple/Ripple → XRP
- BNB/BNB Chain → BNB
- Cardano/Cardano → ADA
- Dogecoin/Dogecoin → DOGE
- Polkadot/Polkadot → DOT
- Avalanche/Avalanche → AVAX
- Polygon/Polygon → POL
- Chainlink/Chainlink → LINK
- Litecoin/Litecoin → LTC
- Uniswap → UNI
- Aave → AAVE
- Toncoin → TON
- Shiba Inu/Shiba Inu → SHIB
- Sui → SUI
- Aptos → APT
- Arbitrum → ARB
- Optimism → OP
- Jupiter → JUP
- Celestia → TIA
- If it is not in the list, use WebSearch to confirm the token symbol
Identify category
- L1 public chains: BTC, ETH, SOL, ADA, AVAX, TON, SUI, APT
- L2 scaling: ARB, OP, POL
- DeFi: UNI, AAVE, LINK, JUP
- Meme: DOGE, SHIB
- Payments: XRP, LTC
- Cross-chain/interoperability: DOT
- Modularity: TIA
- Other: confirm via WebSearch
Determine key variables (all subsequent Agents will need to use these)
- {token}: token symbol (e.g. BTC, ETH)
- {token_name}: full token name (e.g. Bitcoin, Ethereum)
- {category}: category (e.g. L1, DeFi, Meme)
- {project_website}: project official website URL
- {competitors}: 2-3 main competitors in the same category

If the project official website or category cannot be determined, first use one WebSearch for a quick lookup,do not skip this step。

Phase 1: Parallel data collection (5 Subagents)

Key requirement: The following 5 Tasks must be placed inthe same messageto ensure parallel execution.

Each Agent uses subagent_type: "general-purpose"。

Agent 1: Price and technical indicators

description: "Collect {token} price data"

prompt template:

你是加密货币价格分析师。请获取 {token_name}({token}) 近7天的价格数据，并**重点突出最近24小时的变化**。

任务:
1. 使用 WebSearch 搜索 "{token} price last 7 days" 获取最近行情
2. 使用 WebSearch 搜索 "{token} price today 24h" 获取最新24小时详细数据
3. 使用 WebSearch 搜索 "{token} funding rate perpetual" 获取永续合约资金费率
4. 整理以下信息:

   **最近24小时行情:**
   - 当前价格、24h最高、24h最低
   - 24h涨跌幅与涨跌金额
   - 24h成交量与成交额，较前日放量/缩量比例
   - 永续合约资金费率（正=多头支付，负=空头支付）
   - 与BTC同期涨跌幅对比（BTC相关性）
   - 24h内是否有影响价格的即时事件

   **近7天汇总:**
   - 每日收盘价和涨跌幅
   - 7天累计涨跌幅
   - 成交量变化趋势 (放量/缩量)
   - 关键技术信号 (如有: 均线多空排列、RSI超买超卖、明显支撑位/阻力位)
   - 与BTC同期涨跌幅对比

输出要求:
- 以结构化格式返回，**24h行情单独列出**
- 重点突出: 24h涨跌幅、7天涨跌幅、量价配合、资金费率方向、BTC相关性
- 控制在 600 字以内
- 不要给出投资建议
- **标注数据来源**: 关键数据注明来源网站名称（如 CoinGecko、CoinMarketCap、TradingView 等）及原始链接

Agent 2: News and community sentiment

description: "Search for recent news on {token_name}"

prompt template:

你是加密货币新闻与情绪分析师。请搜索 {token_name}({token}) 最近7天的重要新闻和社区情绪。

任务:
1. 使用 WebSearch 搜索以下关键词 (至少搜3次不同关键词):
   - "{token_name} news this week" 或 "{token_name} 最新新闻"
   - "{token} crypto twitter" 或 "{token} community sentiment"
   - "crypto fear greed index today"
2. 从搜索结果中挑选 3-5 条最重要的新闻
3. 使用 WebFetch 访问其中至少 2 条新闻的原文，验证内容真实性
4. 获取当前 Crypto Fear & Greed Index 数值
5. 分析社区情绪倾向

输出要求:
- 列出 3-5 条关键新闻，每条包含: 日期、标题、来源名称、**原文URL**、简要内容(1-2句)
- Crypto Fear & Greed Index: 当前数值及级别 (Extreme Fear / Fear / Neutral / Greed / Extreme Greed)
- 社区情绪判断: 正面 / 负面 / 中性，并说明理由
- 识别是否有重大事件 (协议升级、安全事件、监管动态、合作公告、交易所上下架等)
- 控制在 600 字以内

Agent 3: Category comparative analysis

description: "Analyze the {category} sector situation"

prompt template:

你是加密货币赛道分析师。请分析 {token_name}({token}) 所在的 {category} 赛道近期情况。

任务:
1. 使用 WebSearch 搜索:
   - "{category} crypto sector performance this week" 或 "{category} 赛道 近期表现"
   - "{token_name} vs {competitors} comparison"
2. 整理以下信息:
   - {category} 赛道近期整体趋势 (上升/下行/平稳)
   - 影响赛道的关键因素 (技术升级、TVL变化、用户增长、政策等)
   - 2-3 个主要竞品的近期价格表现和关键动态
   - {token_name} 在赛道中的市值排名和相对地位

输出要求:
- 赛道趋势概述 (2-3句)
- 竞争格局简表: 代币名、近7天涨跌、市值、关键动态
- 该代币的相对优劣势 (1-2条)
- 控制在 500 字以内
- **标注数据来源**: 竞品价格及市值数据注明来源（如 CoinMarketCap、CoinGecko 等）及链接

Agent 4: Crypto market environment

description: "Analyze the crypto market environment"

prompt template:

你是加密货币宏观市场分析师。请分析当前加密货币市场整体环境，重点关注与 {token_name}({token}) 相关的市场因素。

任务:
1. 使用 WebSearch 搜索最新市场数据:
   - "bitcoin dominance total crypto market cap today"
   - "crypto market overview this week"
   - "DXY dollar index today"
   - "bitcoin ETF fund flow this week"
2. 评估:
   - BTC 主导率 (Bitcoin Dominance) 及趋势
   - 加密货币总市值及7日变化
   - 美元指数 (DXY) 水平及走势
   - BTC 现货 ETF 资金流向 (净流入/流出)
   - 美联储利率政策最新动态
   - 是否有重大监管事件

输出要求:
- 加密市场环境一句话总结
- BTC主导率及含义 (资金在BTC vs 山寨币的分配)
- 总市值水平和趋势
- ETF资金流和机构情绪
- DXY与利率环境对加密市场的影响
- 控制在 400 字以内
- **标注数据来源**: 各市场指标注明来源（如 Alternative.me、Farside Investors、Trading Economics 等）及链接

Agent 5: Project fundamentals

description: "Research the fundamentals of the {token_name} project"

prompt template:

你是加密货币项目研究员。请调研 {token_name}({token}) 的项目基本面和链上数据。

任务:
1. 使用 WebFetch 访问项目官网: {project_website}
   - 查看最新公告、路线图更新
2. 使用 WebSearch 搜索:
   - "{token_name} tokenomics supply schedule"
   - "{token_name} on-chain metrics active addresses TVL"
   - "{token_name} github development activity"
3. 整理以下信息:

   **代币经济学:**
   - 总供应量 / 流通供应量 / 流通率
   - 近期是否有大额解锁事件
   - 通胀/通缩机制 (如有)

   **链上指标:**
   - 活跃地址数趋势 (如有)
   - TVL (DeFi/L1适用)
   - 哈希率 (PoW适用) 或质押率 (PoS适用)

   **开发活跃度:**
   - GitHub 近期提交频率或重大更新 (如有)
   - 近期协议升级计划

输出要求:
- 项目最新官方动态
- 代币经济学关键数据
- 链上指标概要
- 控制在 400 字以内
- 如果官网无法访问，说明情况并依赖搜索结果
- **标注数据来源**: 链上数据注明来源（如 Glassnode、DeFiLlama、官网等）及访问URL

Phase 2: Comprehensive analysis (main thread)

After all 5 Agents have returned, complete the following analysis on the main thread.

Step 1: Information Aggregation

Integrate the results from the 5 Agents and identify:

Between dimensions, consistency signals (e.g., price up + community bullish + sector trending up = strongly bullish)
Between dimensions, contradictory signals (e.g., price up but funding rate extremely high = possible overheating)
At the same time, compile all thesource URLsreturned by each Agent, and aggregate them into the source list for the "References" section at the end of the report

Step 2: Causal Attribution

Analyze the causes of price changes, ranked by impact:

Project-level factors: protocol upgrades, security incidents, partnership announcements, token unlocks
Sector transmission factors: sector rotation, competitor events, changes in technical narrative
Market environment factors: BTC trend driven, ETF fund flows, macroeconomic policy, regulatory events

Pay special attention to changes in the last 24 hours: The crypto market operates 24/7; conduct separate attribution analysis for the gains and losses over the last 24 hours, distinguishing short-term catalysts from medium-term trend factors.

Step 3: Trend Forecast

Based on the above analysis, provide:

Short-term outlook (1-2 weeks): consider technical signals + funding rate + upcoming events
Medium-term outlook (1-3 months): consider project fundamentals + sector trends + market cycle
Main risk points: factors that may cause a trend reversal

Phase 3: Output Report

Output the final report in the following HTML format. Use inline CSS to ensure good display in both browsers and Feishu:

<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>{token_name} ({token}) 综合分析报告</title>
<style>
  body { font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; color: #1a1a1a; background: #f8f9fa; }
  .report { background: #fff; border-radius: 12px; padding: 32px; box-shadow: 0 2px 12px rgba(0,0,0,0.08); }
  h1 { font-size: 24px; border-bottom: 3px solid #1a73e8; padding-bottom: 12px; }
  h2 { font-size: 18px; color: #1a73e8; margin-top: 28px; border-left: 4px solid #1a73e8; padding-left: 10px; }
  h3 { font-size: 15px; color: #333; margin-top: 16px; }
  .meta { color: #666; font-size: 13px; margin-bottom: 16px; }
  .summary { background: #e8f0fe; border-radius: 8px; padding: 16px; font-size: 16px; font-weight: 500; margin: 16px 0; }
  .daily-highlight { background: #fff8e1; border: 1px solid #ffcc02; border-radius: 8px; padding: 16px; margin: 16px 0; }
  .daily-highlight h2 { color: #f57f17; border-left-color: #f57f17; }
  table { width: 100%; border-collapse: collapse; margin: 12px 0; font-size: 14px; }
  th { background: #f1f3f4; text-align: left; padding: 10px 12px; font-weight: 600; border-bottom: 2px solid #ddd; }
  td { padding: 8px 12px; border-bottom: 1px solid #eee; }
  tr:hover td { background: #f8f9fa; }
  .up { color: #2e7d32; font-weight: 600; }
  .down { color: #d32f2f; font-weight: 600; }
  .tag { display: inline-block; padding: 2px 8px; border-radius: 4px; font-size: 12px; font-weight: 500; }
  .tag-positive { background: #e8f5e9; color: #2e7d32; }
  .tag-negative { background: #ffebee; color: #c62828; }
  .tag-neutral { background: #f5f5f5; color: #616161; }
  .risk { background: #fff3e0; border-radius: 8px; padding: 12px 16px; margin: 8px 0; }
  .onchain { background: #f3e5f5; border-radius: 8px; padding: 16px; margin: 16px 0; }
  .onchain h2 { color: #7b1fa2; border-left-color: #7b1fa2; }
  .disclaimer { margin-top: 24px; padding-top: 16px; border-top: 1px solid #eee; color: #999; font-size: 12px; }
  .references { margin-top: 16px; padding: 16px 20px; background: #f8f9fa; border-radius: 8px; border-top: 1px solid #eee; }
  .references h3 { font-size: 13px; color: #888; font-weight: 600; margin: 0 0 8px 0; }
  .references ol { margin: 0; padding-left: 18px; }
  .references li { font-size: 12px; color: #999; margin: 3px 0; line-height: 1.5; }
  a.src { color: #1a73e8; text-decoration: none; font-size: 12px; }
  a.src:hover { text-decoration: underline; }
  ul, ol { padding-left: 20px; }
  li { margin: 6px 0; line-height: 1.6; }
</style>
</head>
<body>
<div class="report">

<h1>{token_name} ({token}) 综合分析报告</h1>
<div class="meta">分析日期: {date} | 分析周期: 近7天 | 赛道: {category}</div>

<div class="summary">{一句话总结}</div>

<!-- 最近24小时行情 — 黄色高亮区块，放在最前面 -->
<div class="daily-highlight">
<h2>最近24小时行情</h2>
<table>
  <tr><th>指标</th><th>数值</th></tr>
  <tr><td>当前价格</td><td>$...</td></tr>
  <tr><td>24h最高 / 最低</td><td>$... / $...</td></tr>
  <tr><td>24h涨跌</td><td><span class="up/down">+/-X.XX%</span> (±$金额)</td></tr>
  <tr><td>24h成交量</td><td>$XXX亿 (较前日 +/-XX%)</td></tr>
  <tr><td>资金费率</td><td>+/-X.XX% (多头/空头支付)</td></tr>
  <tr><td>BTC同期表现</td><td>+/-X.XX% (相关性: 强/中/弱)</td></tr>
</table>
<p><strong>24h变动归因:</strong> 简要说明最近24小时涨跌的直接原因</p>
</div>

<h2>一、7日价格概览</h2>
<table>
  <tr><th>指标</th><th>数值</th></tr>
  <tr><td>当前价格</td><td>$XXX</td></tr>
  <tr><td>7日涨跌幅</td><td><span class="up/down">+/-X.XX%</span></td></tr>
  <tr><td>同期BTC表现</td><td>+/-X.XX%</td></tr>
  <tr><td>市值 / 排名</td><td>$XXX亿 / #XX</td></tr>
  <tr><td>成交量趋势</td><td>放量/缩量/持平</td></tr>
  <tr><td>技术面信号</td><td>...</td></tr>
</table>

<h2>二、价格变动原因分析</h2>
<h3>项目层面因素</h3>
<ol><li>...</li></ol>
<h3>赛道传导因素</h3>
<ol><li>...</li></ol>
<h3>市场环境因素</h3>
<ol><li>...</li></ol>

<h2>三、新闻与社区情绪</h2>
<table>
  <tr><th>日期</th><th>事件</th><th>来源</th><th>影响</th></tr>
  <tr><td>...</td><td>...</td><td><a href="原文URL" class="src">来源名称</a></td><td><span class="tag tag-positive/negative/neutral">利好/利空/中性</span></td></tr>
</table>
<p>Fear & Greed Index: <strong>XX — 级别</strong></p>
<p>社区情绪: <strong>正面/负面/中性</strong></p>

<h2>四、赛道对比</h2>
<table>
  <tr><th>代币</th><th>7日涨跌</th><th>市值</th><th>关键动态</th></tr>
  <tr><td>{token_name}</td><td>...</td><td>...</td><td>...</td></tr>
  <tr><td>竞品A</td><td>...</td><td>...</td><td>...</td></tr>
  <tr><td>竞品B</td><td>...</td><td>...</td><td>...</td></tr>
</table>

<div class="onchain">
<h2>五、链上指标与代币经济学</h2>
<h3>链上指标</h3>
<ul>
  <li>活跃地址: ...</li>
  <li>TVL: $XXX (适用于DeFi/L1)</li>
  <li>哈希率/质押率: ...</li>
</ul>
<h3>代币经济学</h3>
<ul>
  <li>流通量/总供应量: XXX / XXX (流通率 XX%)</li>
  <li>近期解锁: ...</li>
  <li>通胀/通缩机制: ...</li>
</ul>
</div>

<h2>六、市场环境</h2>
<ul>
  <li>BTC主导率: XX% (资金偏向BTC/山寨币)</li>
  <li>加密总市值: $X.XX万亿 (7日变化: +/-XX%)</li>
  <li>DXY (美元指数): XXX (强势/弱势)</li>
  <li>BTC ETF 资金流: 本周净流入/流出 $XXX亿</li>
  <li>关键宏观因素: ...</li>
</ul>

<h2>七、趋势展望</h2>
<h3>短期 (1-2周)</h3>
<ul><li>...</li></ul>
<h3>中期 (1-3月)</h3>
<ul><li>...</li></ul>
<h3>主要风险</h3>
<div class="risk">
<ol><li>...</li></ol>
</div>

<div class="references">
<h3>参考来源</h3>
<ol>
  <li>价格数据: <a href="URL" class="src">来源名称（如 CoinGecko / CoinMarketCap）</a></li>
  <li>新闻: <a href="URL" class="src">来源1</a> / <a href="URL" class="src">来源2</a></li>
  <li>链上数据: <a href="URL" class="src">来源名称（如 Glassnode / DeFiLlama）</a></li>
  <li>Fear & Greed Index: <a href="URL" class="src">来源名称（如 Alternative.me）</a></li>
  <li>市场数据 (BTC主导率 / ETF资金流等): <a href="URL" class="src">来源名称（如 Farside Investors）</a></li>
</ol>
</div>

<div class="disclaimer">声明: 本报告由 AI 自动生成，仅供参考，不构成任何投资建议。加密货币波动剧烈，投资有风险，决策需谨慎。</div>
</div>
</body>
</html>

HTML filling rules:

When cryptocurrency price change is positive, use class="up"(green); when negative, use class="down"(red) — note this is opposite to A-shares, following international convention
News impact tags: for bullish use tag-positive, for bearish use tag-negative, for neutral use tag-neutral
For the on-chain metrics section use class="onchain"(purple background)
Replace placeholders in the template with actual data, delete comments
Ensure the HTML is complete and can be opened directly in a browser
The "References" section must be filled with the actual URLs returned by each Agent; the "Source" column of the news table must include clickable links to the original text

Save the report as a file: {token_name}-analysis-{date}.html, saved in the current working directory.

Phase 4: Generate PDF Report

Based on the HTML file generated in Phase 3, print the PDF via Chrome headless:

"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
  --headless --disable-gpu --no-sandbox \
  --print-to-pdf="$(pwd)/{token_name}-analysis-{date}.pdf" \
  --no-pdf-header-footer \
  "file://$(pwd)/{token_name}-analysis-{date}.html"

Note: If the system does not have Chrome, you can use npx -y md-to-pdf "$(pwd)/{token_name}-analysis-{date}.html" as an alternative.

Finally output two files:

./{token_name}-analysis-{date}.html — HTML version (can be opened in a browser)
./{token_name}-analysis-{date}.pdf — PDF version (can be shared directly)

Error Handling

Agent timeout or failure: If an Agent does not return a result, mark that dimension as "data missing" in the report, and analyze the remaining dimensions as usual
Token name cannot be identified: Prompt the user to confirm the token name or symbol
Official website inaccessible: Skip official website scraping, rely on search engine results
Inconsistent data sources: Use the majority data source as the standard, and note data discrepancies in the report

Notes

Strictly limit the word count of each Agent's output to prevent main thread context overflow
The comprehensive analysis stage focuses on cross-correlation, rather than simply listing items
Causal analysis should distinguish between "correlation" and "causation"
Trend forecasts must clearly indicate uncertainty
The crypto market operates 24/7, and time references are based on UTC
Price rise/fall colors follow international convention (green for rise, red for fall), which differs from A-share analysis

About this skill

When to Use

Phase 0: Parse input

Phase 1: Parallel data collection (5 Subagents)

Agent 1: Price and technical indicators

Agent 2: News and community sentiment

Agent 3: Category comparative analysis

Agent 4: Crypto market environment

Agent 5: Project fundamentals

Phase 2: Comprehensive analysis (main thread)

Step 1: Information Aggregation

Step 2: Causal Attribution

Step 3: Trend Forecast

Phase 3: Output Report

Phase 4: Generate PDF Report

Error Handling

Notes