sf-datacloud-harmonize
sf-datacloud-harmonize is a Data warehousing & modelling skill for AI agents, published by Jaganpro in the sf-skills repository on GitHub. Skillspace rates sf-datacloud-harmonize D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Salesforce Data Cloud Harmonize phase. TRIGGER when: user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. DO NOT TRIGGER when: the task is only about streams/DLOs (use sf-datacloud-prepare), segments/insights (use sf-datacloud-segment), retrieval/search (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 423
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 78 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Salesforce Data Cloud harmonization via sf data360 CLI
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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