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Get Started Free →加密货币Skill - 提供BTC、ETH等主流币种行情、K线数据、市场概览 via AkShare/币安/火币
.claude/skills/aifinlab-akshare-crypto/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 58% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 12% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -21% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -38% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 74% | 0% |
| 属性 | 内容 | |:---|:---| | 名称 | akshare-crypto | | 版本 | 1.1.0 | | 分类 | 加密货币 | | 状态 | ✅ 已上线 | | 维护者 | FinClaw Core Team | | 最后更新 | 2026-03-19 |
加密货币Skill，提供比特币(BTC)、以太坊(ETH)等主流加密货币的实时行情、历史K线数据、市场概览。支持多交易所数据。
| 用户输入 | 识别意图 | 调用函数 | |:---|:---|:---| | 比特币价格多少？ | crypto_quote | crypto_quote.py BTC | | 以太坊行情 | crypto_quote | crypto_quote.py ETH | | BTC历史走势 | crypto_hist | crypto_hist.py BTC | | 加密货币市场 | crypto_market | crypto_market.py |
| 数据类型 | 主要来源 | 备用来源 | 认证要求 | |:---|:---|:---|:---:| | 实时行情 | AkShare-币安 | AkShare-火币 | 无需 | | 历史K线 | AkShare-币安 | AkShare-火币 | 无需 | | 市场概览 | CoinMarketCap | - | 无需 |
| 币种 | 代码 | 类型 | 市值排名 | |:---|:---|:---|:---:| | 比特币 | BTC | 原生币 | 1 | | 以太坊 | ETH | 智能合约平台 | 2 | | 泰达币 | USDT | 稳定币 | 3 | | 币安币 | BNB | 交易所代币 | 4 | | 瑞波币 | XRP | 支付协议 | 5 | | 索拉纳 | SOL | 智能合约平台 | 6 | | 卡尔达诺 | ADA | 智能合约平台 | 7 | | 狗狗币 | DOGE | Meme币 | 8 | | 波卡 | DOT | 跨链协议 | 9 | | Polygon | MATIC | Layer2 | 10 |
bash python scripts/crypto_quote.py BTC python scripts/crypto_quote.py ETH
bash python scripts/crypto_hist.py BTC --period 1d --limit 365
bash python scripts/crypto_market.py
| 脚本名 | 功能 | 入口点 | |:---|:---|:---:| | crypto_quote.py | 加密货币行情 | ✅ | | crypto_hist.py | 历史K线数据 | ✅ | | crypto_market.py | 市场概览 | ✅ |
| 类型 | 代表 | 特点 | |:---|:---|:---| | 原生币 | BTC | 价值存储、数字黄金 | | 智能合约平台 | ETH, SOL, ADA | 支持DApp和DeFi | | 稳定币 | USDT, USDC | 锚定美元，波动小 | | 交易所代币 | BNB | 交易平台权益 | | Meme币 | DOGE, SHIB | 社区驱动，波动大 |
加密货币市场全天候24/7交易，无涨跌幅限制。
markdown--- 📊 **数据来源**: AkShare-币安/火币 ⏱️ **数据时间**: 2026-03-19 📌 **交易对**: BTC/USDT 🔗 **原始来源**: Binance/火币交易所 🔧 **分析工具**: FinClaw v1.0 ⚠️ **风险提示**: 加密货币波动极大，投资需谨慎
akshare>=1.10.0
pandas>=1.3.0
pyyaml>=5.4.0| 版本 | 日期 | 变更内容 | |:---|:---:|:---| | 1.1.0 | 2026-03-19 | 符合FinClaw数据规范v1.0 | | 1.0.0 | 2026-03-13 | 初始版本 |
本Skill遵循 FinClaw 数据规范 v1.0 | 数据来源强制标注 | 禁止训练数据编造
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-16 | pass→pass | 10,582 | 2,783 | -74% | 1 | 1 | 0% | 1,590 | 1,690 | +6% | 0 | 0 | — |
case-01 | fail→pass | 10,366 | 7,253 | -30% | 1 | 1 | 0% | 1,537 | 2,426 | +58% | 0 | 0 | — |
case-02 | fail→fail | 14,821 | 22,935 | +55% | 1 | 1 | 0% | 2,874 | 4,867 | +69% | 0 | 0 | — |
case-03 | fail→fail | 20,965 | 14,653 | -30% | 1 | 1 | 0% | 3,240 | 3,647 | +13% | 0 | 0 | — |
case-04 | fail→pass | 9,327 | 3,067 | -67% | 1 | 1 | 0% | 1,634 | 1,835 | +12% | 0 | 0 | — |
case-05 | fail→pass | 13,347 | 3,737 | -72% | 1 | 1 | 0% | 2,512 | 1,987 | -21% | 0 | 0 | — |
case-06 | fail→pass | 16,211 | 3,007 | -81% | 1 | 1 | 0% | 2,937 | 1,812 | -38% | 0 | 0 | — |
case-07 | pass→pass | 14,746 | 13,030 | -12% | 1 | 1 | 0% | 2,288 | 3,459 | +51% | 0 | 0 | — |
case-08 | pass→pass | 9,732 | 6,530 | -33% | 1 | 1 | 0% | 1,552 | 2,297 | +48% | 0 | 0 | — |
case-09 | pass→pass | 7,286 | 3,550 | -51% | 1 | 1 | 0% | 981 | 1,782 | +82% | 0 | 0 | — |
case-10 | fail→pass | 7,330 | 3,719 | -49% | 1 | 1 | 0% | 1,147 | 1,991 | +74% | 0 | 0 | — |
case-22 | fail→fail | 20,373 | 21,132 | +4% | 1 | 1 | 0% | 2,808 | 5,395 | +92% | 0 | 0 | — |
case-11 | fail→pass | 8,557 | 2,875 | -66% | 1 | 1 | 0% | 1,249 | 1,735 | +39% | 0 | 0 | — |
case-12 | fail→pass | 16,987 | 5,308 | -69% | 1 | 1 | 0% | 2,370 | 2,109 | -11% | 0 | 0 | — |
case-13 | fail→pass | 19,604 | 4,357 | -78% | 1 | 1 | 0% | 2,498 | 2,179 | -13% | 0 | 0 | — |
case-14 | pass→pass | 15,384 | 14,105 | -8% | 1 | 1 | 0% | 2,492 | 3,173 | +27% | 0 | 0 | — |
case-15 | fail→pass | 15,713 | 7,586 | -52% | 1 | 1 | 0% | 2,267 | 2,524 | +11% | 0 | 0 | — |
case-17 | pass→pass | 10,367 | 4,933 | -52% | 1 | 1 | 0% | 1,761 | 2,216 | +26% | 0 | 0 | — |
case-18 | fail→pass | 8,110 | 1,994 | -75% | 1 | 1 | 0% | 1,245 | 1,631 | +31% | 0 | 0 | — |
case-19 | pass→pass | 14,199 | 9,034 | -36% | 1 | 1 | 0% | 1,878 | 2,571 | +37% | 0 | 0 | — |
case-20 | fail→fail | 13,109 | 11,233 | -14% | 1 | 1 | 0% | 1,937 | 3,416 | +76% | 0 | 0 | — |
case-21 | fail→fail | 24,706 | 32,841 | +33% | 1 | 1 | 0% | 5,132 | 6,650 | +30% | 0 | 0 | — |
case-23 | fail→fail | 28,001 | 43,431 | +55% | 1 | 1 | 0% | 5,416 | 8,114 | +50% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +43 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.