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Get Started Free →实时监控 - 持续跟踪自选股行情,设置价格提醒
.claude/skills/bilal140202-realtime-monitor/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-14 | ✗→✓ | ▲ Improved | 1% | 0% |
| case-11 | ✓→✗ | ▼ Worse | -45% | 0% |
| case-15 | ✓→✗ | ▼ Worse | -41% | 0% |
| case-21 | ✓→✗ | ▼ Worse | -40% | 0% |
| case-03 | ✗→✗ | = Same ✗ | -4% | 0% |
你是一个股票实时监控助手,能够帮助用户跟踪一组自选股的实时行情,并在价格变化时提供及时的信息更新。
用户可以通过以下方式触发:
从用户输入中提取:
使用 get_quotes_by_query 批量查询:
json{ "tool": "get_quotes_by_query", "arguments": { "queries": ["茅台", "腾讯", "苹果"] } }
或使用分市场精确查询:
json{ "tool": "get_a_share_quotes", "arguments": { "codes": ["sh600519"] } }
json{ "tool": "get_hk_quotes", "arguments": { "codes": ["00700"] } }
json{ "tool": "get_us_quotes", "arguments": { "codes": ["AAPL"] } }
markdown## 📱 自选股实时行情 更新时间:HH:MM:SS | 股票 | 现价 | 涨跌幅 | 今开 | 最高 | 最低 | 成交额 | |------|------|--------|------|------|------|--------| | 贵州茅台 | 1474.92 | +3.36% | 1445 | 1476 | 1443 | 12.6亿 | | 腾讯控股 | 388.6 | +1.25% | 385 | 390 | 384 | 25.3亿 | | 苹果公司 | 185.5 | -0.45% | 186 | 187 | 185 | - | 📊 **异动提醒**: - 🔥 贵州茅台今日涨幅超过 3%,创近期新高
如果用户提供了买入价格:
markdown## 💰 持仓盈亏一览 | 股票 | 现价 | 买入价 | 盈亏比例 | 盈亏金额(假设100股) | |------|------|--------|----------|---------------------| | 贵州茅台 | 1474.92 | 1400 | +5.35% | +7,492 元 | | 腾讯控股 | 388.6 | 350 | +11.03% | +3,860 港元 | 📈 **持仓总评**:整体盈利,表现良好
自动检测并提醒:
用户可以说:"当茅台跌破 1400 时提醒我"
AI 记录条件,并在后续查询时检查:
markdown⚠️ **价格触发提醒**: 贵州茅台当前价格 1395.50,已跌破你设置的 1400 关注价位!
配合 OpenClaw 的定时任务功能,可实现定时推送:
yaml# OpenClaw 定时任务配置 schedules: stock-monitor: cron: "*/5 9-15 * * 1-5" # 交易时间每 5 分钟 skill: realtime-monitor input: stocks: ["600519", "00700", "AAPL"]
用户:帮我看一下持仓情况:茅台买入价 1400,腾讯买入价 350
AI:
get_quotes_by_query 查询茅台和腾讯| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | fail→fail | 10,717 | 2,955 | -72% | 1 | 1 | 0% | 1,513 | 1,450 | -4% | 0 | 0 | — |
case-01 | fail→fail | 12,703 | 7,396 | -42% | 1 | 1 | 0% | 2,193 | 1,515 | -31% | 0 | 0 | — |
case-02 | fail→fail | 16,787 | 5,620 | -67% | 1 | 1 | 0% | 2,646 | 1,556 | -41% | 0 | 0 | — |
case-04 | fail→fail | 6,187 | 1,432 | -77% | 1 | 1 | 0% | 416 | 1,393 | +235% | 0 | 0 | — |
case-05 | fail→fail | 13,288 | 4,280 | -68% | 1 | 1 | 0% | 2,453 | 1,421 | -42% | 0 | 0 | — |
case-06 | fail→fail | 11,524 | 2,190 | -81% | 1 | 1 | 0% | 1,439 | 1,442 | +0% | 0 | 0 | — |
case-07 | fail→fail | 14,831 | 5,170 | -65% | 1 | 1 | 0% | 2,551 | 1,457 | -43% | 0 | 0 | — |
case-08 | fail→fail | 10,367 | 6,578 | -37% | 1 | 1 | 0% | 2,053 | 1,507 | -27% | 0 | 0 | — |
case-09 | fail→fail | 10,467 | 4,761 | -55% | 1 | 1 | 0% | 1,535 | 1,383 | -10% | 0 | 0 | — |
case-10 | fail→fail | 9,734 | 2,655 | -73% | 1 | 1 | 0% | 1,410 | 1,504 | +7% | 0 | 0 | — |
case-11 | pass→fail | 16,565 | 4,963 | -70% | 1 | 1 | 0% | 2,532 | 1,398 | -45% | 0 | 0 | — |
case-12 | fail→fail | 17,067 | 2,376 | -86% | 1 | 1 | 0% | 2,274 | 1,463 | -36% | 0 | 0 | — |
case-13 | fail→fail | 13,901 | 7,147 | -49% | 1 | 1 | 0% | 2,365 | 1,644 | -30% | 0 | 0 | — |
case-14 | fail→pass | 12,710 | 9,985 | -21% | 1 | 1 | 0% | 2,361 | 2,389 | +1% | 0 | 0 | — |
case-15 | pass→fail | 13,295 | 6,487 | -51% | 1 | 1 | 0% | 2,567 | 1,518 | -41% | 0 | 0 | — |
case-16 | fail→fail | 13,203 | 5,432 | -59% | 1 | 1 | 0% | 2,192 | 1,379 | -37% | 0 | 0 | — |
case-17 | fail→fail | 6,695 | 9,289 | +39% | 1 | 1 | 0% | 1,089 | 1,733 | +59% | 0 | 0 | — |
case-18 | fail→fail | 53,196 | 10,615 | -80% | 1 | 1 | 0% | 6,059 | 1,994 | -67% | 0 | 0 | — |
case-19 | fail→fail | 21,852 | 22,934 | +5% | 1 | 1 | 0% | 3,699 | 5,208 | +41% | 0 | 0 | — |
case-20 | fail→fail | 10,909 | 5,482 | -50% | 1 | 1 | 0% | 1,604 | 1,414 | -12% | 0 | 0 | — |
case-21 | pass→fail | 12,359 | 5,329 | -57% | 1 | 1 | 0% | 2,237 | 1,349 | -40% | 0 | 0 | — |
case-22 | fail→fail | 18,386 | 6,836 | -63% | 1 | 1 | 0% | 3,246 | 1,428 | -56% | 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. 22 cases were attempted, and 9 counted toward the lift figure. The other 13 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -9 percentage points is the difference between those two pass rates over the 9 comparable cases. 7 cases got worse with the skill loaded, and they are included in that figure.
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.