B2C Logs
ListedAnalyze B2C customer journey data from Salesforce Commerce Cloud to identify trends and optimize experiences for increased conversions.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add salesforcecommercecloud/b2c-developer-tooling --skill b2c-logs -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto 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.
Automated safety checks
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About this skill
What it does
This skill enables AI agents to retrieve and analyze backend logs from Salesforce B2C Commerce instances. It provides direct access to system events, error messages, and operational data necessary for troubleshooting and performance monitoring.
When to use it
- Diagnosing checkout failures or transaction errors in a live production environment.
- Investigating unexpected spikes in server latency or response times.
- Auditing security events or suspicious user activity within the commerce platform.
- Validating that recent deployments did not introduce critical bugs or regressions.
Key capabilities
- Access to backend log streams from Salesforce B2C Commerce instances.
- Retrieval of specific log entries based on time ranges or severity levels.
- Parsing of structured data for root cause analysis.
Example prompts
- "Pull the last 100 error-level logs from the production instance between 9:00 AM and 10:00 AM today."
- "Search the logs for any occurrences of 'PaymentGatewayException' in the past hour."
- "Summarize the top three recurring errors found in the system logs over the last 24 hours."
Tips & gotchas
Ensure you have appropriate permissions to access the target B2C Commerce instance before running queries, as log data may contain sensitive customer information. Always specify clear time ranges to avoid retrieving excessive historical data that could slow down analysis.