Using Datahub

by datahub-projectc6d0ded76ecaNo license42 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 8 days ago

This skill provides routing guidance for all DataHub interaction skills. It is injected at session start and helps map user intent to the correct skill. Do not invoke this skill directly — it is loaded automatically.

Instructions onlyAI & Agents
AI-generated overview

Routing guide that maps DataHub catalog requests to the correct DataHub interaction skill.

What it does
This skill is a routing guide for five DataHub catalog interaction skills: Search, Enrich, Lineage, Quality, and Setup. It provides a routing table mapping user intents to the appropriate skill and command, plus disambiguation rules for ambiguous requests. It also documents CLI attribution conventions for datahub commands. It is loaded automatically at session start and is not meant to be invoked directly.
When to use it
Use it when a request involves the DataHub catalog and you need to decide which DataHub skill should handle it. It is intended for intent routing rather than direct execution of catalog operations.
Requirements
Requires the DataHub skill set it references and, for the CLI attribution guidance, the datahub CLI. It ships no scripts; it is instructions only.

Using DataHub Skills

You have access to 5 DataHub catalog interaction skills. Use this guide to route the user's request to the correct skill.


Skill Routing Table

User IntentSkillCommand
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 connectionSetup/datahub-setup
Configure default scopes and profilesSetup/datahub-setup

Disambiguation Rules

When the intent is ambiguous, use these rules:

"Tag" requests

  • All tag operations (PII, sensitive, important, reviewed, team-x) → Enrich (general metadata)

"Domain" requests

  • Filter search to a domain → Search (scoped search)
  • Configure default domain → Setup (profile configuration)

"Quality" or "health" requests

  • Failing assertions, active incidents, health status → Quality
  • Create assertions, run quality checks, raise incidents → Quality
  • Subscribe to assertion failures or incidents → Quality
  • Metadata quality/documentation/ownership coverage → Use Search to gather the data and synthesize the answer

Lineage vs. Search

  • "What feeds into X" / "what depends on X" / "impact of changing X" → Lineage
  • "What dashboards use table X" → Lineage (relationship traversal)
  • "Who owns X" / "what is X" → Search (metadata lookup)

Setup vs. other skills

  • "Set up" / "install" / "authenticate" / "verify connection" → Setup
  • "Configure defaults" / "set default platform" / "create profile" → Setup
  • "Check if DataHub is working" → Setup (connectivity verification)

CLI Attribution

When running datahub CLI commands, pass -C skill=<name> on the root command so usage can be attributed:

bash
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.


Critical Rules

  1. Never guess the skill. If the intent is genuinely ambiguous, ask the user to clarify.
  2. One skill per request unless the user explicitly asks for multiple operations.
  3. Lineage is for lineage only — not for general "what is this entity?" questions (that's Search).
  4. Search handles ad-hoc questions. "Who owns X?" and "what columns does X have?" are Search questions, not Lineage.
  5. Enrich handles all metadata writes — descriptions, tags, glossary terms, ownership, deprecation.
  6. Quality handles data quality — assertions, incidents, health checks, subscriptions.
  7. Setup handles environment and configuration — CLI install, auth, connectivity, default scopes.

Source and attribution

Source:datahub-project/datahub-skillsinskills/using-datahubat commitc6d0ded

License: No license

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