diff --git a/finance/payment-market-breakdown.md b/finance/payment-market-breakdown.md
new file mode 100644
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+---
+name: Payment market breakdown
+description: Analyze approval rates and blocked revenue by market and card type. Surfaces underperforming card-market combos and quantifies the recovery opportunity.
+icon: activity
+---
+
+# Goal
+
+Show where `{{company.name}}`'s payment performance breaks down by market and card type, quantify the blocked revenue, and give specific recommendations. No database or additional setup required — works from the payments API alone.
+
+# Steps
+
+1. Parse `$ARGUMENTS` for `days=N` (default 30) and `min_txns=N` (minimum transactions per group to suppress noise, default 5).
+
+2. Compute the start timestamp: `{{today}}` minus `days` days at 00:00:00 UTC.
+
+3. Fetch all transactions in the window by paginating `fluid_api("/api/payment/v2026-04/transactions?per_page=100&page=N", "GET")` until no more pages. Only include records where `created_at >= start`.
+
+4. For each transaction, determine the country:
+   - Use `metadata.country_code` if present.
+   - Otherwise infer from `currency_code` using this map: USD→US, EUR→DE, GBP→GB, AUD→AU, CAD→CA, BRL→BR, MXN→MX, SGD→SG, INR→IN, TWD→TW, JPY→JP, KRW→KR. If the currency doesn't map, mark the country as `—`.
+
+5. Compute overall stats across all transactions where `action` is `purchase` or `authorize`:
+   - Total attempts, successful count, declined count, approval rate (%)
+   - Total successful revenue in USD-equivalent (use the raw `amount_cents` sum — note this will be inflated for non-USD; flag that in the report)
+   - Total blocked revenue (sum of `amount_cents` for declined transactions)
+   - Refund count and refund rate (refunds / successful purchases)
+
+6. Group remaining transactions by `currency_code × card_network × country`. For each group with at least `min_txns` attempts, compute:
+   - Attempt count
+   - Approval rate (%)
+   - Successful revenue (sum of amount_cents for successful records, in local currency)
+   - Blocked revenue (sum of amount_cents for declined records, in local currency)
+   - Refund rate
+
+7. Flag a group if: approval rate < 80% OR it accounts for more than 10% of total blocked revenue.
+
+8. For each flagged group, generate a one-sentence recommendation using this logic:
+   - Low approval + EUR/GBP/CAD/AUD: "Consider adding a local payment method (SEPA, PayPal, or regional debit) as an alternative for [country] customers."
+   - Low approval + amex: "Amex has elevated decline rates in [country]. Offering Mastercard or Visa as preferred checkout options may recover this revenue."
+   - Low approval + USD: "Investigate whether a gateway routing rule or fraud filter is applying incorrectly to [card_network] in the US."
+   - Low approval + any: "Review gateway configuration for [card_network] transactions in [country] — decline rates are above baseline."
+   - High refund rate (>10%): "High refund rate for [card_network]/[country] may indicate fulfillment or fraud patterns worth investigating."
+
+9. Render the report in this structure:
+
+```
+[Company] — Payment Market Breakdown
+Window: last [N] days  |  [X] total transactions fetched
+
+OVERALL
+  Approval rate    XX%
+  Blocked revenue  [currency] X,XXX  (raw sum — non-USD amounts not converted)
+  Refund rate      X%
+
+BY MARKET × CARD TYPE  (min [N] transactions)
+
+  Currency  Country  Card    Attempts  Approval  Blocked
+  --------  -------  ------  --------  --------  -------
+  ...rows sorted by blocked revenue descending...
+
+FLAGGED COMBOS
+  For each flagged group: "Currency / Country / Card — XX% approval, X,XXX blocked"
+  → [Recommendation]
+
+WHAT THIS REPORT COULD SHOW WITH ORDER + SUBSCRIPTION DATA
+  - Which products have the highest payment failure rates (high-value items declining
+    more than average suggests a fraud filter problem, not a card problem)
+  - Subscription MRR sitting on underperforming card types — quantify churn risk
+    before it happens
+  - Customer LTV by card type and market — if Amex customers are worth 2x, optimizing
+    their approval rate has outsized revenue impact
+  - Retry success rate — of declined transactions, which ones were later recovered
+    through a retry or dunning flow
+```
+
+10. If there are no flagged groups, say so — it means payment performance looks healthy across all markets. If there are fewer transactions than `min_txns` in every group, lower the threshold and re-run, or note that more transaction history is needed.
diff --git a/manifest.json b/manifest.json
index a30cf1b..8125ede 100644
--- a/manifest.json
+++ b/manifest.json
@@ -1,6 +1,15 @@
 {
   "version": 1,
   "skills": [
+    {
+      "slug": "finance/payment-market-breakdown",
+      "name": "Payment market breakdown",
+      "description": "Analyze approval rates and blocked revenue by market and card type. Surfaces underperforming card-market combos and quantifies the recovery opportunity.",
+      "category": "finance",
+      "icon": "activity",
+      "path": "finance/payment-market-breakdown.md",
+      "updated_at": "2026-07-31T00:00:00Z"
+    },
     {
       "slug": "finance/promo-code-summary",
       "name": "Promo code summary",