From datahub-skills
Routes user intents to the correct DataHub interaction skill (search, enrich, lineage, quality, setup). Automatically loaded at session start to disambiguate requests.
How this skill is triggered — by the user, by Claude, or both
Slash command
/datahub-skills:using-datahubThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You have access to 5 DataHub catalog interaction skills. Use this guide to route the user's request to the correct skill.
You have access to 5 DataHub catalog interaction skills. Use this guide to route the user's request to the correct skill.
| User Intent | Skill | Command |
|---|---|---|
| Find or discover entities (search, browse, filter, list) | Search | /datahub-search |
| Answer a question about the catalog ("who owns X?", "how many X?") | Search | /datahub-search |
| Update metadata (descriptions, tags, glossary terms, ownership, deprecation) | Enrich | /datahub-enrich |
| Explore lineage (upstream, downstream, impact, root cause, dependencies) | Lineage | /datahub-lineage |
| Data quality (assertions, incidents, health checks) | Quality | /datahub-quality |
| Notifications (subscribe to assertion failures, incidents) | Quality | /datahub-quality |
| Install CLI, authenticate, verify connection | Setup | /datahub-setup |
| Configure default scopes and profiles | Setup | /datahub-setup |
When the intent is ambiguous, use these rules:
When running datahub CLI commands, pass -C skill=<name> on the root command so usage can be attributed:
datahub -C skill=datahub-search search "revenue"
datahub -C skill=datahub-enrich graphql --query '...'
datahub -C skill=datahub-lineage lineage --urn "..."
Use the skill name from the YAML frontmatter. If -C is not recognized, omit it — the command works the same without it.
npx claudepluginhub datahub-project/datahub-skills --plugin datahub-skillsSearches DataHub catalog to discover datasets, find entities by platform/domain, and answer ad-hoc questions about metadata ownership and PII.
Interviews users about their datasets and databases to generate reusable data context skills that document schema, entities, metrics, and domain knowledge.
Governs SAP Datasphere catalogs: enriches metadata, manages glossaries, defines KPIs, controls tags, analyzes lineage impacts. Improves discoverability and self-service analytics.