Shopify workflow4 prompts · one store

Audit a Shopify store's detected app stack.

This workflow returns one verified Shopify app-stack audit.

Open one compact store lookup, separate exact app relationships from supporting technology signals and turn the result into a concise stack brief.

9apps detected

Example run · 13 Oct 2026 · <1 min

Published by Spytrend · 29 Sep 2026 · Methodology

Run in order

A 4-step Shopify technology audit

Prompts update with the store domain and use compact technology evidence only.

Confirm the merchant

Normalize the domain and verify the canonical Shopify merchant surface.

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Prompt 01
Audit detected Shopify apps for this store: allbirds.com.au. Focus: complete detected app stack.

Normalize exactly one public merchant domain. Reject invalid or infrastructure domains. Never substitute fuzzy, related, regional, campaign, account, shop or subdomain matches. Do not call tools.

Return only the retained domain and evidence boundary: `Detected technology may be incomplete. Not returned does not mean an app is not installed or used.` Stop after Step 1.
Read the compact exact-domain record

Retain every exact returned app label and keep supporting signals separate.

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Prompt 02
Cost guard: before each paid Spytrend call, run the free `estimate_cost` with the same tool and arguments, estimate the cost and stay within the user's stated budget; if the user has not stated a budget, tell them the estimate before the first paid call. If pricing consent is required, show the returned terms and stop until the customer explicitly agrees; never accept on the customer's behalf. If a required call does not fit the stated budget, make no paid call and return `Budget limit prevents required research`; omit an optional call that does not fit and disclose reduced coverage. When opening ads with `get_ad`, skip multilang ads (`is_multilang`) and never call `get_media` after `get_ad`. Retry once only when `retryable=true`, after `retry_after_seconds`. Read `params.ignored` after every search; an ignored required filter never counts as applied. Cost notices are not part of the final customer report.
Run search_shops(q=<exact normalized host>, platform="Shopify", exclude_infrastructure=true, limit=5). Accept only the row whose normalized host exactly equals the submitted host.

Never call get_shop, search_ads, get_ad or get_advertiser. Retain Shopify identity, exact app names and identifiers/categories. Keep pixels, analytics, theme, plan, review, messaging, payment, checkout and tracker fields as Supporting technology. Preserve every returned app but do not call the list complete.

Return only concise retained evidence and lookup status. Hide calls, IDs, quotas, timing and fuzzy rows. Stop after Step 2.
Group the stack

Organize only supported relationships by customer-facing function.

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Prompt 03
Using retained evidence only, classify the submitted domain as Qualified, Limited evidence or Unresolved. Missing data is Not returned, never absent or unused. Keep Exact detected apps separate from Supporting technology. Do not merge similar names or infer functions without returned support.

Set execution status to Complete when the required exact-domain lookup completed and its required filters were applied, including when no exact row or only sparse technology was returned. Use Partial only when that required lookup failed or a required filter was ignored. Evidence incompleteness stays in Evidence limits and does not by itself make execution Partial.

Return only the classification and retained evidence groups. Stop after Step 3.
Write the technology audit

Return the snapshot, inspection questions and explicit evidence limits.

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Prompt 04
Write the final answer from retained evidence only. Do not make more tool calls.

Use `# Shopify App Stack Audit: allbirds.com.au`, show the classification plus Complete/Partial, then state: `Detected technology may be incomplete. Not returned does not mean an app is not installed or used.` Show Store status, Exact detected apps, Supporting technology, three inspection questions and Evidence limits. Do not show comparison or overlap sections.

Preserve the retained execution status exactly. Do not change Complete to Partial merely because detected technology may be incomplete or fields were not returned.

Use no tables and stay within 260 words. Hide the service name, internal labels, calls, IDs, quotas, timing, retries and run summaries. Do not infer active use, configuration, performance, revenue, ROAS or profitability.

End exactly: `Detected technology is an observed relationship, not proof of active configuration, usage, completeness, quality, conversions, revenue, ROAS or profitability.`

Stop after Step 4.
Use the complete workflow in one promptAll evidence rules in one copyable promptView promptHide prompt
Complete workflow
Cost guard: before each paid Spytrend call, run the free `estimate_cost` with the same tool and arguments, estimate the cost and stay within the user's stated budget; if the user has not stated a budget, tell them the estimate before the first paid call. If pricing consent is required, show the returned terms and stop until the customer explicitly agrees; never accept on the customer's behalf. If a required call does not fit the stated budget, make no paid call and return `Budget limit prevents required research`; omit an optional call that does not fit and disclose reduced coverage. When opening ads with `get_ad`, skip multilang ads (`is_multilang`) and never call `get_media` after `get_ad`. Retry once only when `retryable=true`, after `retry_after_seconds`. Read `params.ignored` after every search; an ignored required filter never counts as applied. Cost notices are not part of the final customer report.
Use the connected Spytrend MCP to audit detected Shopify app relationships for **allbirds.com.au**. Focus: **complete detected app stack**.

Execute every research stage in this prompt in one turn. Apart from mandatory pre-call cost notices, do not emit intermediate step responses and do not stop after validation. Stop early only for invalid input, unavailable required evidence or unresolved required identity. Return only the final customer report.

## Inputs and evidence

1. Accept exactly one public merchant domain. Normalize its host. Reject infrastructure, localhost, IP addresses and invalid domains. If it is invalid, return exactly `Invalid controlled input configuration` and make no MCP call.
2. Run exactly one compact lookup: `search_shops(q=<exact normalized host>, platform="Shopify", exclude_infrastructure=true, limit=5)`.
3. Accept only a row whose normalized host exactly equals the submitted host. Never substitute a related, regional, campaign, account, shop, subdomain or fuzzy-matched domain.
4. Never call `get_shop`, `search_ads`, `get_ad` or `get_advertiser`. A missing exact row or sparse technology remains unresolved or limited evidence.
5. Retain explicit Shopify identity, exact app display names and returned app identifiers/categories. Keep pixels, analytics, theme, plan, review, email/SMS, payment, checkout and tracker fields in a separate Supporting technology block. Country and traffic are optional context, not app-stack evidence.
6. Preserve every app returned in the compact exact-domain row. Deduplicate only identical normalized display names. Never call the returned list complete.

## Classification

7. Classify the domain as Qualified, Limited evidence or Unresolved. Qualified requires the exact Shopify domain and at least one focus-relevant technology field. Limited evidence means the exact Shopify domain resolved but focus-relevant technology is missing, empty or ambiguous. Unresolved means no exact row, a domain conflict or unconfirmed Shopify identity.
8. Missing data is `Not returned`, never zero, not installed or not used. Never promote supporting technology into Exact detected apps.
9. Do not merge similar app names, vendors or functions. Group by function only when returned categories or a maintained catalog relationship supports it.

## Customer answer

10. Return `# Shopify App Stack Audit: allbirds.com.au` and the classification plus Complete/Partial.
11. Immediately add: `Detected technology may be incomplete. Not returned does not mean an app is not installed or used.`
12. Show Store status, Exact detected apps, Supporting technology, three concrete inspection questions and Evidence limits. Do not show comparison or overlap sections.
13. Show every exact app name in Exact detected apps and the relevant returned fields in Supporting technology.
14. Keep the answer table-free and within 260 words. Hide service name, preset/workflow/search-set names, taxonomy slugs, route and tool names, calls, parameters, raw IDs, JSON, quotas, tokens, timing, retries, run summaries and fuzzy rows.
15. Label an explicitly returned stable first-party link `Evidence`. Never construct one.
16. Mark Partial only when the required lookup failed. A completed lookup with no exact row or sparse technology is Complete with Limited/Unresolved classification.
17. Never rank stack quality or infer maturity, optimization, active use, conversions, revenue, ROAS or profitability.

End exactly:

`Detected technology is an observed relationship, not proof of active configuration, usage, completeness, quality, conversions, revenue, ROAS or profitability.`
Example output

A 9-app snapshot for allbirds.com.au.

The domain resolved as an exact root-domain Shopify merchant. The store record returned nine exact app relationships across support, email, reviews, page building, checkout and storefront navigation, plus pixels and a theme as supporting technology.

Evidence boundaryThe result describes returned detections. It does not confirm active configuration, plan level or implementation quality.
Detected stack highlightsExample run · 13 Oct 2026
9

Exact detected apps

Gorgias, Klaviyo, PageFly, Shop Pay, Yotpo, Yotpo: Product Reviews App, meteor-mega-menu, mw-bundle-builder and starapps-variant-image.

6

Supporting signals

Facebook Pixel, TikTok Pixel, Google Ads, Google Analytics, Google Tag Manager and the theme Allbirds AU v14.1, kept outside the app count.

1

Exact-domain lookup

Qualified and Complete from one store lookup. Regional and subdomain rows were not substituted.

Store domain: allbirds.com.au · exact apps: 9
Key findings

What the snapshot makes inspectable.

01

Exact versus supporting

Exact app names drive the count. Supporting technology fields reinforce context without being promoted into exact matches.

02

Functional overlap

Multiple measurement and experimentation detections make event ownership and data flow useful implementation questions.

03

Known gaps

Operational use, configuration, plan level and stack completeness remain Not confirmed.

Methodology

How detected technology is qualified.

Published by Spytrend from a dated, bounded example.

Merchant identity

Only a compact row whose normalized host exactly matches the submitted merchant can qualify.

Eligibility

Exact list first

Every exact app label returned in the compact row is preserved before functional grouping; the detected list may be incomplete.

Primary evidence

Supporting signals

Messaging, reviews, payments and trackers stay separate unless they reinforce an exact relationship.

Evidence boundary

Adaptive output

Unresolved eligibility, sparse stacks and truncated responses receive explicit fallback states.

Failure handling
FAQ

Questions about this workflow.

Does detection prove that an app is active?

No. A returned relationship is a detection snapshot and does not confirm current configuration, plan level or implementation quality.

What is an exact app relationship?

It is a display name returned in the store profile app list. Supporting fields are reported separately and never added to the exact count.

What happens when Shopify status is unclear?

The workflow reports eligibility as Not confirmed and does not present an app-stack conclusion.

Why can product counts differ?

Compact technology fields may be incomplete. A relationship that was not returned cannot be treated as absent or unused.

Can the workflow prove revenue or ROAS?

No. Technology detection does not establish sales, conversions, revenue, ROAS or profitability.

Spytrend MCP

Inspect a Shopify app stack from live data.

Connect Spytrend MCP, enter a store domain and run the four prompts in one AI chat.