Hire an AI product data gaps and catalogue review

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• Problem counts for each check, against last month
• Products with no cost, clashing SKUs and impossible stock, with names
• The 15 thinnest listings and what each is missing
• Products missing from a channel or from every collection

How it does the job well

• Work from the real catalogue, prices, stock and policies. Check variants and currencies.
• Judge changes by contribution margin, not revenue alone.
• Change one thing at a time on a live store and keep a way to roll back.
• Keep product claims consistent with supplier data and labels.

Mistakes it avoids

• Running the renaming step without a map the owner agreed.
• Calling a zero-stock product a stock error. The skill looks for negative or impossible numbers only.
• Fixing everything in one go. Do costs and SKUs first, then re-check.
• Running on a store with a handful of products. A manual look is faster.
• Editing live products, prices or themes without approval or a backup.
• Ignoring shipping, returns and fees when judging profit.

What a good result looks like

An example, not your task: You have dozens of products or more and nobody checks the data on a schedule.

• This month. The problem count for each check, set against last month.
• Fix first. Products with no cost, clashing SKUs and impossible stock, with names and a plain fix.
• Listings to improve. The 15 thinnest listings and what each one is missing.
• Not selling where it should. Products missing from a channel or from every collection.
• Stuck. Problems that have stayed open for three months or more.
• Skipped. Any check not run, and why.

How the work is checked

• Costs, SKUs and stock were read in that order.
• Every count is set against last month, or the baseline run is stated.
• Nothing was edited, published, deleted or moved without a yes.
• The renaming step, if run, showed the changes first and named the link risk.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Read last month. Opens the saved counts and channel list, or marks this as the baseline run.
• Costs, then identifiers, then stock. Finds missing costs, then clashing SKUs, then impossible stock. Clashing SKUs can cause stock errors, so they come first.
• Check the listings. Scores every active product on description, images, search fields, weight, barcode and cost, and lists the worst 15.
• Check where products show. Finds live products missing from a channel and products in no collection.
• Choose the optional steps. Runs the naming fix only with your map and your yes. Looks for unused files every third month.
• Compare and loop. Marks each problem new, still open or fixed. After you fix, it re-checks that item, at most twice, then stops.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id monthly-catalogue-clean-up-keeper only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/monthly-catalogue-clean-up-keeper/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• A connection to your Shopify store, or a product export
• The sales channels every live product should appear on, the first time
• A naming map for sizes and colours, if you want mixed names fixed (optional)

Helpful context (optional)

• Your list of sales channels
• Sales by product, to rank the channel and collection gaps

Tools and access

• Claude Code: It can keep the catalogue folder and run on the 1st of each month.
• Shopify: The skills read products, stock and channels from the store connection.
• Claude, ChatGPT or Gemini with a Shopify connection: Lets the AI read your live stock levels with read-only access.
• Any good chat AI: Works on an exported inventory file if you have no connection.

Functions and deliverables

• Product data gaps and catalogue review: Find missing costs, duplicate stock codes and thin listings. Compare earlier issues and get a ranked fix list.
  • Problem counts for each check, against last month
  • Products with no cost, clashing SKUs and impossible stock, with names
  • The 15 thinnest listings and what each is missing
  • Products missing from a channel or from every collection
• Shopify missing product cost finder: Connect Shopify read access to find variants with missing or zero costs. Get a worklist and the limits of the audit.
  • A list of variants with no cost
  • The count of missing costs and their share of your catalogue
  • The retail value of the stocked items with no cost
  • A top vendors list to share the clean-up work
  • A CSV file, or a JSON summary if you ask for it
  Source: 40rty AI.
• Shopify duplicate SKU and barcode finder: Find Shopify variants that share a SKU or barcode. Get grouped clashes and optional blank-SKU findings to review before making changes.
  • A list of duplicate SKUs and barcodes
  • The products and variants that clash
  • Blank SKU flags (optional)
  • Plain or JSON output
  Source: 40rty AI.
• Shopify stock sync error finder: Check Shopify stock counts by location and get a CSV of possible stock sync issues.
  • A summary table by location with counts of each kind of flag
  • A list of products with negative available stock
  • A list of products with more committed than on hand
  • A CSV of every flagged product, or the same rows in the chat
  • A short "where to look first" list, with likely causes marked as guesses
  Source: 40rty AI.
• Product listing completeness checker: Score each active Shopify product on missing descriptions, images, SEO, weight, barcode and cost. Get a product data completeness report, worst first.
  • A completeness score for each product
  • The missing fields on each product
  • A list ordered worst first
  • Totals for each type of gap
  Source: 40rty AI.
• Product sales channel availability checker: Find live Shopify products missing from Online Store, Google Shopping or Meta. Give it your store domain and get a list to fix. It only reads data.
  • A list of all sales channels
  • Active products missing from required channels
  • A report you can fix from
  • Assurance that nothing was changed
  Source: 40rty AI.
• Orphan product finder: Find products in no collection and products in too many, so shoppers can find them. Give it your Shopify store and get a CSV report.
  • Products in no collection
  • Products in too many collections
  • Collection names and sizes
  • A report you can act on
  Source: 40rty AI.
• Product variant name editor: Get mixed names like Sm, Small and S fixed to one standard. Changes live variants and may break saved links.
  • A preview of every variant that would change
  • Bulk updates after your approval
  • A count of changes made
  • A JSON report (optional)
  Source: 40rty AI.
• Unused store file finder: Get files in your store that no product, page or post uses, so you can clear out clutter.
  • A list of unused files with links and sizes
  • Total space the unused files take up
  • A sample of the oldest orphans
  • A JSON version for a spreadsheet (optional)
  Source: 40rty AI.
• Brand profile builder: Share your website. Get a reusable profile covering your products, customers, voice and approved claims, with sources.
  • A folder of eight plain files, from a start file for your AI to a claims list and a change log
  • A tag on every fact, and every claim marked approved, pending or banned
  • A two-sentence diagnosis of your biggest gap, and a list of what's missing and who can answer it
  • A short slice for your next step, if you name one

Tasks you can use it for

• You have dozens of products or more and nobody checks the data on a schedule.
• Your margin or stock reports have looked off and you suspect missing costs.
• You want to be sure every live product is on every channel you sell on.

Limits to check before starting

• Your store has only a handful of products: look through them by hand, it is faster.
• You want the agent to fix products for you: it only reads and lists fixes, so make the changes in your store admin.
• You need a one-off check of one problem, such as clashing SKUs: run the single skill, such as the Shopify duplicate SKU and barcode finder, instead.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Add the agent in Claude Code (a paid tool), or save it in .claude/agents, and connect your store. The connection needs read access from your store admin, and your plan or the connector may limit or charge for it. Without one, paste a product export. The monthly run starts when you ask for it, or from a scheduled task you set up.
• The first time, tell it which channels every live product should be on.
• Ask it to run this month's check. Fix costs and SKUs first.
• Tell it what you fixed. It re-checks those items and shows the new count.
• Run it again next month. It shows what is new, still open or fixed.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/monthly-catalogue-clean-up-keeper for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.