Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-discount-hygiene-cleanupgit clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/40rty-ai/shopify-admin-skills/shopify-admin-discount-hygiene-cleanup)<a href="https://agentmods.dev/skills/40rty-ai/shopify-admin-skills/shopify-admin-discount-hygiene-cleanup"><img src="https://agentmods.dev/badge/skills/40rty-ai/shopify-admin-skills/shopify-admin-discount-hygiene-cleanup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/40rty-ai/shopify-admin-skills/shopify-admin-discount-hygiene-cleanup"><img src="https://agentmods.dev/badge/skills/40rty-ai/shopify-admin-skills/shopify-admin-discount-hygiene-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.01468 |
| Opus 5.5 | $0.00013 | $0.00587 |
| Sonnet 5.5 | $0.00006 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
Grade A, and why
shopify-admin-discount-hygiene-cleanup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Audits the discount catalog for expired codes, codes with zero redemptions, and duplicate code prefixes. Discount sprawl accumulates over months of campaigns and makes the admin difficult to navigate. Optionally deletes flagged codes. Replaces manual discount cleanup and builds on the discount-ab-analysis skill with a write step.
Prerequisites
- Authenticated Shopify CLI session:
shopify store auth --store <domain> --scopes read_discounts,write_discounts - API scopes:
read_discounts,write_discounts
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| store | string | yes | — | Store domain (e.g., mystore.myshopify.com) |
| flag_expired | bool | no | true | Flag/delete discounts past their end date |
| flag_zero_usage | bool | no | true | Flag/delete discounts with 0 redemptions older than N days |
| zero_usage_min_age_days | integer | no | 30 | Age threshold for zero-usage flags |
| dry_run | bool | no | true | Preview without executing mutations |
| format | string | no | human | Output format: human or json |
Safety
⚠️
discountCodeDeletepermanently removes discount codes. Deleted codes cannot be recovered. Customers who received a deleted code will find it invalid. Run withdry_run: trueto review the flagged list before committing. Always check that expired codes are not referenced in active email campaigns before deleting.
Workflow Steps
-
OPERATION:
discountNodes— query Inputs:first: 250, selectdiscount { ... on DiscountCodeBasic { codes, usageLimit, asyncUsageCount, endsAt, status } }, pagination cursor Expected output: All discount codes with usage and expiry data; paginate untilhasNextPage: false -
Flag discounts matching:
flag_expired(status = EXPIRED) and/orflag_zero_usage(asyncUsageCount == 0 AND created >zero_usage_min_age_daysago) -
OPERATION:
discountCodeDelete— mutation Inputs:id: <discount_node_id>Expected output:deletedCodeDiscountId,userErrors
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 186 lines · 32 tokens per session scan A 0e322b476e72
shopify-admin-discount-hygiene-cleanup is a skill published in the GitHub repository 40RTY-ai/shopify-admin-skills (200 stars, last pushed 7d ago), licensed MIT. It adds 32 tokens to every session and 1,468 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-13.
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