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B2C Metadata

Listed
salesforcecommercecloud·vlatest·marketing·Apache-2.0

This B2C Metadata skill extracts and manages product data for personalized customer experiences, boosting engagement & conversions.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add salesforcecommercecloud/b2c-developer-tooling --skill b2c-metadata -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

salesforcecommercecloud

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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scanned

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Not scanned. none of the 11 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as salesforcecommercecloud/b2c-developer-tooling.
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About this skill

The b2c-metadata skill provides access to Business-to-Consumer (B2C) metadata within the Salesforce Commerce Cloud ecosystem. It enables AI agents to retrieve, analyze, and manage product, customer, and order data structures essential for e-commerce operations. This tooling bridges the gap between raw backend data and actionable insights for automated decision-making.

When to use it

  • Retrieving real-time product catalog information for dynamic pricing or recommendation engines.
  • Analyzing customer profile attributes to personalize marketing campaigns automatically.
  • Validating order metadata against current inventory levels before fulfillment processes begin.
  • Debugging data inconsistencies by querying specific schema definitions within the B2C environment.

Key capabilities

  • Access to structured B2C metadata relevant to Salesforce Commerce Cloud instances.
  • Support for querying product, customer, and transactional data entities.
  • Integration with developer tooling pipelines for automated data verification.

Example prompts

  • "Fetch the latest metadata schema for all active products in the North American region."
  • "Retrieve customer segmentation tags associated with high-value accounts from the B2C database."
  • "Validate the order status metadata for transaction ID 12345 against current inventory records."

Tips & gotchas

Ensure your AI agent has appropriate read permissions configured within the Salesforce Commerce Cloud instance before attempting to query sensitive customer or financial metadata. Limit queries to specific data subsets to prevent performance bottlenecks in high-traffic environments.