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Get Started Free →A股换手率分析/筹码松动分析。当用户说"换手率"、"turnover"、"筹码"、"换手率异常"、"筹码松动"时触发。量化分析换手率变化含义。支持formal和brief风格。
.claude/skills/aifinlab-a-share-turnover-analysis/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-16 | ✗→✓ | ▲ Improved | -56% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -44% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -64% | 0% |
| case-01 | ✓→✗ | ▼ Worse | -70% | 0% |
| case-13 | ✓→✗ | ▼ Worse | -67% | 0% |
bashSCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts" python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [日期] python "$SCRIPTS/cn_stock_data.py" quote --code [CODE] python "$SCRIPTS/cn_stock_data.py" finance --code [CODE]
| 维度 | formal | brief | |------|--------|-------| | 换手统计 | 完整统计+分布 | Z-score | | 量价配合 | 历史模式分析 | 当日模式 | 默认风格：brief。
python# 调用 skill result = run_skill({ "param1": "value1", "param2": "value2" })
bashpython scripts/run_skill.py --input data.json
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→fail | 20,792 | 13,758 | -34% | 1 | 1 | 0% | 3,200 | 973 | -70% | 0 | 0 | — |
case-02 | fail→fail | 13,808 | 12,675 | -8% | 1 | 1 | 0% | 2,255 | 1,048 | -54% | 0 | 0 | — |
case-03 | fail→fail | 19,993 | 7,527 | -62% | 1 | 1 | 0% | 3,186 | 931 | -71% | 0 | 0 | — |
case-04 | pass→pass | 16,615 | 16,286 | -2% | 1 | 1 | 0% | 2,566 | 2,995 | +17% | 0 | 0 | — |
case-05 | pass→pass | 20,693 | 18,381 | -11% | 1 | 1 | 0% | 3,062 | 3,098 | +1% | 0 | 0 | — |
case-06 | pass→pass | 15,578 | 13,240 | -15% | 1 | 1 | 0% | 2,200 | 2,401 | +9% | 0 | 0 | — |
case-16 | fail→pass | 14,116 | 3,549 | -75% | 1 | 1 | 0% | 2,740 | 1,193 | -56% | 0 | 0 | — |
case-17 | fail→pass | 22,570 | 9,653 | -57% | 1 | 1 | 0% | 3,725 | 2,092 | -44% | 0 | 0 | — |
case-07 | pass→pass | 17,559 | 14,377 | -18% | 1 | 1 | 0% | 2,479 | 2,553 | +3% | 0 | 0 | — |
case-08 | pass→pass | 18,206 | 16,273 | -11% | 1 | 1 | 0% | 2,638 | 2,791 | +6% | 0 | 0 | — |
case-09 | pass→pass | 8,708 | 4,244 | -51% | 1 | 1 | 0% | 1,388 | 1,144 | -18% | 0 | 0 | — |
case-10 | pass→pass | 20,660 | 11,999 | -42% | 1 | 1 | 0% | 2,390 | 2,181 | -9% | 0 | 0 | — |
case-11 | pass→pass | 19,272 | 15,269 | -21% | 1 | 1 | 0% | 2,452 | 2,503 | +2% | 0 | 0 | — |
case-12 | pass→pass | 15,791 | 11,568 | -27% | 1 | 1 | 0% | 2,170 | 2,189 | +1% | 0 | 0 | — |
case-13 | pass→fail | 23,061 | 11,539 | -50% | 1 | 1 | 0% | 3,589 | 1,171 | -67% | 0 | 0 | — |
case-14 | pass→pass | 19,501 | 18,213 | -7% | 1 | 1 | 0% | 2,854 | 3,374 | +18% | 0 | 0 | — |
case-15 | fail→pass | 21,062 | 3,357 | -84% | 1 | 1 | 0% | 3,304 | 1,191 | -64% | 0 | 0 | — |
case-18 | pass→pass | 22,239 | 18,134 | -18% | 1 | 1 | 0% | 2,820 | 2,947 | +5% | 0 | 0 | — |
case-19 | pass→pass | 13,937 | 13,945 | +0% | 1 | 1 | 0% | 2,077 | 2,449 | +18% | 0 | 0 | — |
case-20 | pass→fail | 27,397 | 44,965 | +64% | 1 | 1 | 0% | 3,809 | 1,105 | -71% | 0 | 0 | — |
case-21 | pass→fail | 24,805 | 7,571 | -69% | 1 | 1 | 0% | 3,928 | 833 | -79% | 0 | 0 | — |
case-22 | pass→fail | 22,273 | 9,214 | -59% | 1 | 1 | 0% | 4,664 | 1,110 | -76% | 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 15 counted toward the lift figure. The other 7 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 15 comparable cases. 6 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.