
Shopify Admin Discount Cost Trend
- 2 installs
- 173 repo stars
- Updated June 26, 2026
- 40rty-ai/shopify-admin-skills
shopify-admin-discount-cost-trend is a read-only Claude Code skill that tracks total Shopify discount dollars over week, month, or quarter buckets, broken down by discount type and code.
About
This Claude Code skill tracks how much a Shopify store gave away in discounts over time, bucketed by week, month, or quarter and broken down by discount code and type. A finance or store owner runs it to see whether discount spend is trending up or down and which campaigns drive it. It is read-only and exports a CSV of discount cost over time.
- Tracks total discount dollars given over week/month/quarter buckets
- Breaks discount spend down by code and discount type
- Read-only, exporting a longitudinal discount-cost CSV
Shopify Admin Discount Cost Trend by the numbers
- 2 all-time installs (skills.sh)
- Ranked #1,759 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
- Data as of Aug 1, 2026 (Skillselion catalog sync)
shopify-admin-discount-cost-trend capabilities & compatibility
Free skill; requires an authenticated Shopify store session with read_orders
- Capabilities
- discount cost tracking · promotion analytics · spend trend analysis
- Use cases
- data analysis
- Runs
- Runs locally
- Pricing
- Free
What shopify-admin-discount-cost-trend says it does
Tracks how much money the store gave away in discounts over time, bucketed by week, month, or quarter, and broken down by discount code and discount type
Answers: "is our discount spend trending up or down, and which campaigns are driving it?" Read-only — no mutations.
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| Installs | 2 |
|---|---|
| repo stars | ★ 173 |
| Last updated | June 26, 2026 |
| Repository | 40rty-ai/shopify-admin-skills ↗ |
What it does
Track Shopify discount spend over time by code and type to see cost trends.
Who is it for?
Finance owners tracking whether discount spend is rising or falling over time
Skip if: Per-discount ROI or cannibalization analysis, which a separate skill covers
When should I use this skill?
You want a time-series view of total discount cost by code and type
What you get
A bucketed discount-cost trend with per-code and per-type breakdowns.
- discount_cost_trend_<date>.csv with per-bucket and per-code cost
By the numbers
- periods_back defaults to 12
- top_codes defaults to 10
- 1 GraphQL operation (orders query)
Files
Purpose
Tracks how much money the store gave away in discounts over time, bucketed by week, month, or quarter, and broken down by discount code and discount type (percentage / fixed amount / free shipping / automatic). Answers: "is our discount spend trending up or down, and which campaigns are driving it?" Read-only — no mutations. Complements discount-roi-calculator (per-discount return) with a longitudinal view of total cost.
Prerequisites
- Authenticated Shopify CLI session:
shopify store auth --store <domain> --scopes read_orders - API scopes:
read_orders
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| store | string | yes | — | Store domain (e.g., mystore.myshopify.com) |
| period | string | no | month | Bucket size: week, month, or quarter |
| periods_back | integer | no | 12 | Number of buckets to report |
| top_codes | integer | no | 10 | Top discount codes to break out individually; remainder grouped as other |
| include_shipping_discounts | bool | no | true | Whether to count shipping discounts in the totals |
| format | string | no | human | Output format: human or json |
Safety
ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.
Workflow Steps
1. Compute window from period × periods_back (e.g., month × 12 → last 12 calendar months starting from the first day of the bucket 11 months ago)
2. OPERATION: orders — query Inputs: query: "created_at:>='<window_start>' financial_status:paid", first: 250, select createdAt, discountCodes, currentTotalDiscountsSet, totalDiscountsSet, cartDiscountAmountSet, discountApplications { allocationMethod, targetType, value, ... on DiscountCodeApplication { code }, ... on AutomaticDiscountApplication { title }, ... on ManualDiscountApplication { title } }, shippingLines { discountAllocations { allocatedAmountSet } }, pagination cursor Expected output: All paid orders in the window with discount data; paginate until hasNextPage: false
3. For each order, attribute discount cost:
cart_discount=currentTotalDiscountsSet.shopMoney.amountshipping_discount= sum ofshippingLines.discountAllocations.allocatedAmountSet(only ifinclude_shipping_discounts: true)total_discount= cart_discount + shipping_discount- Attribute by code: prefer first
discountApplications.codefor code discounts,titlefor automatic / manual
4. Bucket each order into its period (week-of-year, year-month, or year-quarter) and aggregate:
- Total discount cost per bucket
- Per discount code per bucket
- Per discount type per bucket (percentage, fixed_amount, shipping, automatic)
5. Identify top codes by total cost across the window; aggregate the rest as other
GraphQL Operations
# orders:query — validated against api_version 2025-01
query DiscountCostTrend($query: String!, $after: String) {
orders(first: 250, after: $after, query: $query) {
edges {
node {
id
name
createdAt
discountCodes
currentTotalDiscountsSet { shopMoney { amount currencyCode } }
totalDiscountsSet { shopMoney { amount currencyCode } }
cartDiscountAmountSet { shopMoney { amount currencyCode } }
discountApplications(first: 10) {
edges {
node {
allocationMethod
targetType
targetSelection
value {
... on PricingPercentageValue { percentage }
... on MoneyV2 { amount currencyCode }
}
... on DiscountCodeApplication { code }
... on AutomaticDiscountApplication { title }
... on ManualDiscountApplication { title description }
}
}
}
shippingLines(first: 5) {
edges {
node {
title
discountAllocations {
allocatedAmountSet { shopMoney { amount currencyCode } }
}
}
}
}
}
}
pageInfo { hasNextPage endCursor }
}
}Session Tracking
Claude MUST emit the following output at each stage. This is mandatory.
On start, emit:
╔══════════════════════════════════════════════╗
║ SKILL: Discount Cost Trend ║
║ Store: <store domain> ║
║ Period: <period> × <periods_back> ║
║ Started: <YYYY-MM-DD HH:MM UTC> ║
╚══════════════════════════════════════════════╝After each step, emit:
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>On completion, emit:
For format: human (default):
══════════════════════════════════════════════
DISCOUNT COST TREND (last <periods_back> <period>s)
Total discount cost: $<amount>
Avg per <period>: $<amount>
Latest <period>: $<amount> (<delta_vs_prev_pct>% vs prior)
By bucket:
2025-Q1 $<n> (cart $<n> / shipping $<n>)
2025-Q2 $<n> (cart $<n> / shipping $<n>)
By discount type:
code $<n> (<pct>%)
automatic $<n> (<pct>%)
manual $<n> (<pct>%)
shipping $<n> (<pct>%)
Top codes (by total cost):
"<code>" $<n> (<pct>%)
"<code>" $<n> (<pct>%)
other $<n> (<pct>%)
Output: discount_cost_trend_<date>.csv
══════════════════════════════════════════════For format: json, emit:
{
"skill": "discount-cost-trend",
"store": "<domain>",
"period": "month",
"periods_back": 12,
"total_discount_cost": 0,
"by_bucket": [],
"by_type": { "code": 0, "automatic": 0, "manual": 0, "shipping": 0 },
"top_codes": [],
"currency": "USD",
"output_file": "discount_cost_trend_<date>.csv"
}Output Format
CSV file discount_cost_trend_<YYYY-MM-DD>.csv with columns: bucket, discount_code_or_title, discount_type, orders_count, cart_discount, shipping_discount, total_discount, currency
Error Handling
| Error | Cause | Recovery |
|---|---|---|
THROTTLED | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| Stacked discount codes | Multiple codes on one order | Attribute proportionally to each code by their value share, or label as multi-code if equal |
| Manual discount with no title | Cashier-entered with empty title | Group as manual:untitled |
| Multi-currency orders | Presentment currency != shop currency | Sum on shopMoney.amount (shop currency) for consistency |
Best Practices
- Use
period: weekfor promotional businesses with frequent campaigns;period: monthfor stores with steady evergreen offers;period: quarterfor board reporting. - A flat or rising trend with no campaign activity often points to automatic discount creep — review automatic discounts that have no end date.
- Cross-reference the latest bucket against
discount-roi-calculatorto verify the cost increase is producing matching incremental revenue. - Set
include_shipping_discounts: falseif your accounting books shipping subsidy separately from product discounts. - Set up monthly automation: discount spend that drifts above budget should trigger a finance review before it shows up in margin reports.
Related skills
FAQ
What time buckets are supported?
Week, month, or quarter, set by the period parameter, with periods_back controlling how many buckets are reported (12 by default).
Can shipping discounts be excluded?
Yes, include_shipping_discounts defaults to true but can be turned off to exclude shipping discounts from the totals.