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Get Started Free →Turn a pile of receipts into a filed expense report through a tool-using agent — extraction, policy checks, and categorization done for you; submission gated on your approval. Use when asked to file my expenses, process these receipts, build my expense report, or expense this trip. Produces the itemized report with policy flags and an approval-gated filing plan.
.claude/skills/mohitagw15856-expense-filer/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 69% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 31% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 11% | 0% |
| case-21 | ✗→✓ | ▲ Improved | 39% | 0% |
| case-01 | ✓→✗ | ▼ Worse | 32% | 0% |
Nobody's judgment is improved by hand-typing receipts. This skill does the clerk work — extraction, categorization, policy screening, currency normalization — and stops at the line that matters: submission happens only after a human reads the report. Numbers must reconcile; anything ambiguous is flagged, never guessed.
Ask for these if not provided:
| # | Date | Merchant | Amount | Curr | → report curr] | Category | Receipt | Flags | |---|---|---|---|---|---|---|---|---| Total: n] items · amount] · reconciles ✓ Flags needing you: each with the question to answer]
For agents with file/OCR access and expense-system access (API or UI). Without tools, the report itself is the deliverable. Rules per SKILLSPEC.md §5.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→fail | 13,498 | 12,785 | -5% | 1 | 1 | 0% | 2,391 | 3,146 | +32% | 0 | 0 | — |
case-02 | fail→pass | 8,749 | 8,505 | -3% | 1 | 1 | 0% | 1,333 | 2,253 | +69% | 0 | 0 | — |
case-03 | pass→pass | 8,396 | 5,763 | -31% | 1 | 1 | 0% | 1,250 | 1,845 | +48% | 0 | 0 | — |
case-04 | pass→pass | 9,730 | 7,051 | -28% | 1 | 1 | 0% | 1,409 | 2,129 | +51% | 0 | 0 | — |
case-05 | pass→fail | 7,835 | 5,322 | -32% | 1 | 1 | 0% | 1,220 | 1,753 | +44% | 0 | 0 | — |
case-06 | pass→pass | 10,277 | 5,447 | -47% | 1 | 1 | 0% | 1,694 | 1,816 | +7% | 0 | 0 | — |
case-07 | pass→pass | 7,521 | 5,470 | -27% | 1 | 1 | 0% | 1,171 | 1,777 | +52% | 0 | 0 | — |
case-08 | pass→pass | 9,033 | 5,205 | -42% | 1 | 1 | 0% | 1,413 | 1,842 | +30% | 0 | 0 | — |
case-09 | pass→pass | 5,945 | 5,125 | -14% | 1 | 1 | 0% | 934 | 1,798 | +93% | 0 | 0 | — |
case-10 | pass→pass | 11,237 | 7,339 | -35% | 1 | 1 | 0% | 1,710 | 2,094 | +22% | 0 | 0 | — |
case-11 | pass→pass | 8,972 | 6,848 | -24% | 1 | 1 | 0% | 1,530 | 2,047 | +34% | 0 | 0 | — |
case-12 | pass→pass | 7,174 | 4,413 | -38% | 1 | 1 | 0% | 1,153 | 1,707 | +48% | 0 | 0 | — |
case-13 | pass→pass | 9,146 | 2,575 | -72% | 1 | 1 | 0% | 1,517 | 1,352 | -11% | 0 | 0 | — |
case-14 | pass→pass | 5,545 | 4,759 | -14% | 1 | 1 | 0% | 866 | 1,582 | +83% | 0 | 0 | — |
case-15 | pass→pass | 9,161 | 5,360 | -41% | 1 | 1 | 0% | 1,481 | 1,910 | +29% | 0 | 0 | — |
case-16 | pass→pass | 7,843 | 4,330 | -45% | 1 | 1 | 0% | 1,164 | 1,700 | +46% | 0 | 0 | — |
case-17 | fail→pass | 10,154 | 6,986 | -31% | 1 | 1 | 0% | 1,556 | 2,044 | +31% | 0 | 0 | — |
case-18 | pass→pass | 7,283 | 4,120 | -43% | 1 | 1 | 0% | 1,137 | 1,593 | +40% | 0 | 0 | — |
case-19 | fail→pass | 8,902 | 3,756 | -58% | 1 | 1 | 0% | 1,354 | 1,509 | +11% | 0 | 0 | — |
case-20 | fail→fail | 12,169 | 12,751 | +5% | 1 | 1 | 0% | 2,255 | 3,047 | +35% | 0 | 0 | — |
case-21 | fail→pass | 9,060 | 5,967 | -34% | 1 | 1 | 0% | 1,345 | 1,864 | +39% | 0 | 0 | — |
case-22 | fail→fail | 18,621 | 19,723 | +6% | 1 | 1 | 0% | 3,040 | 3,813 | +25% | 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. The headline lift of +9 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 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.