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Get Started Free →Triggered by "monthly recap", "how did I do this month", "spending summary", "financial review", "weekly recap", "quarterly review", "year in review"
.claude/skills/davepoon-recap/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-17 | ✗→✓ | ▲ Improved | -8% | 0% |
| case-15 | ✓→✗ | ▼ Worse | 13% | 0% |
| case-19 | ✓→✗ | ▼ Worse | -61% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 83% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 62% | 0% |
Generate a narrative financial review for any time period.
$ARGUMENTS for the time span:query MCP tool with compare: "prior_period":json { "period": "<detected_period>", "compare": "prior_period", "include": ["ratios", "anomalies", "accounts"] } (Use start/end if a specific date range was requested.)
json { "start": "<same_period_last_year_start>", "end": "<same_period_last_year_end>", "include": ["ratios"] } For example, if reviewing February 2026, also fetch February 2025.
query MCP tool:json { "recurring": true }
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-10 | fail→fail | 9,809 | 9,026 | -8% | 1 | 1 | 0% | 1,777 | 1,096 | -38% | 0 | 0 | — |
case-01 | fail→fail | 13,706 | 9,226 | -33% | 1 | 1 | 0% | 2,333 | 1,052 | -55% | 0 | 0 | — |
case-02 | fail→fail | 8,612 | 5,987 | -30% | 1 | 1 | 0% | 1,430 | 824 | -42% | 0 | 0 | — |
case-03 | fail→fail | 14,086 | 6,326 | -55% | 1 | 1 | 0% | 2,604 | 1,079 | -59% | 0 | 0 | — |
case-04 | pass→pass | 11,508 | 22,122 | +92% | 1 | 1 | 0% | 1,993 | 3,647 | +83% | 0 | 0 | — |
case-05 | pass→pass | 10,276 | 10,386 | +1% | 1 | 1 | 0% | 1,665 | 2,702 | +62% | 0 | 0 | — |
case-06 | pass→pass | 9,308 | 3,613 | -61% | 1 | 1 | 0% | 871 | 1,268 | +46% | 0 | 0 | — |
case-07 | fail→fail | 3,187 | 7,448 | +134% | 1 | 1 | 0% | 496 | 1,048 | +111% | 0 | 0 | — |
case-08 | fail→fail | 3,442 | 7,325 | +113% | 1 | 1 | 0% | 500 | 826 | +65% | 0 | 0 | — |
case-09 | fail→fail | 2,877 | 7,184 | +150% | 1 | 1 | 0% | 453 | 981 | +117% | 0 | 0 | — |
case-11 | fail→fail | 12,100 | 29,060 | +140% | 1 | 1 | 0% | 1,674 | 960 | -43% | 0 | 0 | — |
case-12 | fail→fail | 12,982 | 7,157 | -45% | 1 | 1 | 0% | 2,471 | 1,062 | -57% | 0 | 0 | — |
case-13 | fail→fail | 16,804 | 5,984 | -64% | 1 | 1 | 0% | 2,991 | 761 | -75% | 0 | 0 | — |
case-14 | fail→fail | 18,479 | 14,433 | -22% | 1 | 1 | 0% | 2,602 | 911 | -65% | 0 | 0 | — |
case-15 | pass→fail | 4,509 | 6,813 | +51% | 1 | 1 | 0% | 756 | 851 | +13% | 0 | 0 | — |
case-16 | fail→fail | 9,284 | 5,316 | -43% | 1 | 1 | 0% | 1,680 | 756 | -55% | 0 | 0 | — |
case-17 | fail→pass | 8,919 | 5,422 | -39% | 1 | 1 | 0% | 1,530 | 1,412 | -8% | 0 | 0 | — |
case-18 | fail→fail | 9,806 | 7,766 | -21% | 1 | 1 | 0% | 1,750 | 976 | -44% | 0 | 0 | — |
case-19 | pass→fail | 14,434 | 25,528 | +77% | 1 | 1 | 0% | 2,088 | 824 | -61% | 0 | 0 | — |
case-20 | fail→fail | 14,440 | 8,106 | -44% | 1 | 1 | 0% | 2,047 | 1,219 | -40% | 0 | 0 | — |
case-21 | fail→fail | 3,696 | 6,225 | +68% | 1 | 1 | 0% | 575 | 974 | +69% | 0 | 0 | — |
case-22 | fail→fail | 12,562 | 6,645 | -47% | 1 | 1 | 0% | 2,116 | 1,027 | -51% | 0 | 0 | — |
case-23 | fail→fail | 14,026 | 6,610 | -53% | 1 | 1 | 0% | 2,608 | 960 | -63% | 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, and 4 counted toward the lift figure. The other 19 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 -4 percentage points is the difference between those two pass rates over the 4 comparable cases. 4 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.