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 CodeInfinity1/Stram --skill shopping-assistantgit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/codeinfinity1/stram/shopping-assistant)<a href="https://agentmods.dev/skills/codeinfinity1/stram/shopping-assistant"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/shopping-assistant/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/codeinfinity1/stram/shopping-assistant"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/shopping-assistant.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 | $0.00028 | $0.00573 |
| Opus 5.5 | $0.00011 | $0.00229 |
| Sonnet 5.5 | $0.00006 | $0.00115 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
shopping-assistant 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 1mo 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shopping Assistant
Purpose
Help the user make informed purchase decisions without autonomously buying anything. This skill turns shopping/e-commerce references into native research, comparison, note, and approval workflows.
When To Use
Use when the user asks to compare products, find options, evaluate specs, inspect reviews, prepare a cart, or decide what to buy.
Inputs And Evidence
- Budget, region, must-have features, nice-to-have features, constraints, and preferred stores.
- Product pages, current prices, shipping/return terms, reviews, and availability.
- User's purchase intent and approval boundary.
Tool Map
research_webpagesfetch_webpagebrowser_live_openbrowser_live_observeweb-data-extractionshopping_comparison_createshopping_comparison_inspectpurchase_intent_preparewrite_notemessage-approval-policy
Workflow
- Clarify budget, constraints, and decision criteria.
- Gather current product evidence from native web/browser tools.
- Compare options by user-relevant dimensions, not only price.
- Use
shopping_comparison_createto preserve products, evidence timing, seller/price/availability, risks, and recommendation as a local artifact. - Use
shopping_comparison_inspectbefore reporting the shortlist or recommendation. - If the user wants a cart/review step, use
purchase_intent_prepareand stop before checkout, payment, order placement, or contacting sellers unless explicitly approved.
Native Implementation Boundaries
- Use Stram web and browser tools.
- Do not import external reference shopping plugins or store-specific upstream scripts.
- Do not use brittle product-name keyword routing; reason from user criteria and page evidence.
- Native commerce tools create research and purchase-review artifacts only; they do not buy, add to cart, or contact sellers.
Safety And Approval
- Purchases, carts, payments, addresses, and seller messages require approval.
- Do not store payment details.
- Verify current prices because they change frequently.
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.
- 1mo ago First seen · 74 lines · 28 tokens per session scan A fce1dd1abb7c
shopping-assistant is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 573 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 2026-08-31.
Other skills, from other repositories
domain-hunter
Search domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check domain prices, find domain deals, compare registrars, or search for .ai/.com domains.
product-match
Find visually or functionally similar products from an image, name, or description. Use when the user asks to "find something like this", match a product from a photo, or source alternates to a given item.
product-pair
Suggest complementary products that pair well with a given item — side tables for sofas, task lights for desks, etc. Use when the user asks "what goes with" a product, wants coordinating pieces, or asks to complete a furniture grouping.
billing-automation
Build automated billing systems for recurring payments, invoicing, subscription lifecycle, and dunning management. Use when implementing subscription billing, automating invoicing, or managing recurring payment systems.
watermark-engine
Generates a watermark overlay system for images and video with configurable positioning, opacity, tiling, and paywall integration for automatic removal on subscription or purchase. Use when user wants to add branding, attribution, or free-tier watermarks to visual content.
monetization
Monetization strategy for iOS/macOS apps. Covers readiness assessment, pricing model selection, tier structuring, free trial strategy, and implementation guidance. Use when deciding what to charge, how to price, or planning monetization end-to-end.