Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Plaid financial data API: bank accounts, transactions, balances, income, assets, identity verification, and ACH payments. Connect to 12,000+ financial institutions for personal finance and lending apps.
.claude/skills/mkurman-plaid-finance/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | -19% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 59% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 6% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-19 | ✗→✓ | ▲ Improved | -36% | 0% |
Plaid connects applications to 12,000+ financial institutions for bank accounts, transactions, balances, income, identity verification, and ACH payments. Standard for fintech apps needing secure financial data access.
bashuv pip install plaid-python
pythonimport plaid from plaid.api import plaid_api config = plaid.Configuration( host=plaid.Environment.Sandbox, api_key={"clientId": "YOUR_CLIENT_ID", "secret": "YOUR_SECRET"}, ) client = plaid_api.PlaidApi(plaid.ApiClient(config)) resp = client.link_token_create(plaid.LinkTokenCreateRequest( user={"client_user_id": "user-123"}, client_name="My App", products=["transactions", "auth"], country_codes=["US"], language="en", )) print(resp.link_token)
pythonresp = client.transactions_sync(plaid.TransactionsSyncRequest(access_token=access_token)) for tx in resp.added: print(f"{tx.date}: {tx.name} — ${tx.amount:.2f}")
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 10,457 | 6,835 | -35% | 1 | 1 | 0% | 2,016 | 1,759 | -13% | 0 | 0 | — |
case-02 | fail→pass | 11,854 | 7,582 | -36% | 1 | 1 | 0% | 2,191 | 1,766 | -19% | 0 | 0 | — |
case-03 | pass→pass | 8,078 | 6,529 | -19% | 1 | 1 | 0% | 1,644 | 1,610 | -2% | 0 | 0 | — |
case-04 | fail→pass | 2,529 | 1,734 | -31% | 1 | 1 | 0% | 347 | 550 | +59% | 0 | 0 | — |
case-17 | pass→pass | 8,869 | 3,002 | -66% | 1 | 1 | 0% | 1,401 | 836 | -40% | 0 | 0 | — |
case-05 | pass→pass | 14,294 | 3,269 | -77% | 1 | 1 | 0% | 2,559 | 932 | -64% | 0 | 0 | — |
case-06 | pass→pass | 8,286 | 3,021 | -64% | 1 | 1 | 0% | 1,530 | 798 | -48% | 0 | 0 | — |
case-07 | pass→pass | 6,354 | 2,631 | -59% | 1 | 1 | 0% | 1,143 | 744 | -35% | 0 | 0 | — |
case-08 | fail→pass | 9,453 | 8,093 | -14% | 1 | 1 | 0% | 1,780 | 1,889 | +6% | 0 | 0 | — |
case-09 | pass→pass | 3,059 | 3,240 | +6% | 1 | 1 | 0% | 413 | 851 | +106% | 0 | 0 | — |
case-10 | fail→pass | 7,463 | 3,514 | -53% | 1 | 1 | 0% | 1,295 | 864 | -33% | 0 | 0 | — |
case-11 | pass→pass | 3,809 | 2,177 | -43% | 1 | 1 | 0% | 623 | 684 | +10% | 0 | 0 | — |
case-12 | pass→pass | 3,616 | 2,289 | -37% | 1 | 1 | 0% | 570 | 704 | +24% | 0 | 0 | — |
case-13 | pass→pass | 5,009 | 2,331 | -53% | 1 | 1 | 0% | 821 | 692 | -16% | 0 | 0 | — |
case-14 | pass→fail | 7,058 | 1,529 | -78% | 1 | 1 | 0% | 1,148 | 570 | -50% | 0 | 0 | — |
case-15 | pass→pass | 3,564 | 2,927 | -18% | 1 | 1 | 0% | 612 | 762 | +25% | 0 | 0 | — |
case-16 | pass→pass | 3,485 | 2,223 | -36% | 1 | 1 | 0% | 578 | 707 | +22% | 0 | 0 | — |
case-18 | pass→pass | 10,562 | 5,120 | -52% | 1 | 1 | 0% | 1,928 | 1,250 | -35% | 0 | 0 | — |
case-19 | fail→pass | 10,090 | 4,699 | -53% | 1 | 1 | 0% | 1,772 | 1,136 | -36% | 0 | 0 | — |
case-20 | pass→pass | 10,011 | 7,500 | -25% | 1 | 1 | 0% | 2,008 | 1,780 | -11% | 0 | 0 | — |
case-21 | pass→pass | 11,610 | 9,109 | -22% | 1 | 1 | 0% | 2,139 | 2,008 | -6% | 0 | 0 | — |
case-22 | pass→pass | 8,780 | 5,983 | -32% | 1 | 1 | 0% | 1,625 | 1,450 | -11% | 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 +18 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is 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.