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setting-up-data-catalog

Populates and maintains a PostHog data catalog with canonical metrics, certifications, and table relationships.

713|118|Updated Aug 11, 2020
Search Tags:#metrics#certification#data catalog#Data Governance#PostHog#table relationships#Semantic Layer
One-click install
npx skills add https://github.com/PostHog/posthog-foss --skill setting-up-data-catalog
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: setting-up-data-catalog
Source: https://github.com/PostHog/posthog-foss/tree/main/products/data_catalog/skills/setting-up-data-catalog
Command: npx skills add https://github.com/PostHog/posthog-foss --skill setting-up-data-catalog

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Teams lose track of what numbers canonically mean, which warehouse tables to trust, and how tables join, because that knowledge lives only in people's heads. This Skill seeds and curates a per-project data catalog (semantic layer) so metrics, trust marks, and relationships are recorded, reviewed, and kept current.

Core Features & Use Cases

  • Catalog seeding: Certify trusted warehouse tables/views, propose evidence-backed table joins with measured match rates, and create canonical metrics from existing PostHog insights.
  • Review queue maintenance: Pull pending metric, relationship, and certification proposals from system.information_schema, summarize their evidence, and promote or reject them via human-confirmed MCP tools.
  • Drift handling: Detect metrics that have diverged from their source insight and re-snapshot or redefine them before approval.
  • Use Case: A data team bootstraps a new PostHog project: the Skill surveys the most-queried tables, proposes certifications for the trusted ones, samples candidate join keys for match-rate evidence, and seeds canonical metrics from the team's most-used insights, all landing as proposals for human approval.

Quick Start

Ask the agent to set up the data catalog for this project by certifying trusted tables, proposing evidenced joins, and seeding canonical metrics from existing insights.

Frequently Asked Questions about setting-up-data-catalog

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a data catalog or semantic layer in PostHog?▼

Work top-down: propose certifications for the warehouse tables the team relies on, propose joins only with sampled match-rate evidence, and seed metrics from the project's most-used insights. Everything lands as unapproved proposals until a human confirms promotion.

How do I certify or deprecate a warehouse table in PostHog?▼

Use the data-catalog certification propose tool with proposed_status 'certified' or 'deprecated' on the target table or view. The proposal stays unapproved until a human settles it with the certification certify or deprecate confirmed-action tools.

Can catalog entries be approved automatically without human review?▼

No. Everything an agent writes lands as unapproved proposals, and promotion tools require a human-typed confirmation via confirmed_action. Proposed or drifted entries must never be treated as canonical.

What happens when a metric drifts from its source insight?▼

A drifted metric has is_drifted set to true and cannot be approved until the drift is cleared. Resolve it by re-snapshotting the insight's current query with the refresh-from-insight tool, or by editing the metric to unlink or redefine it.

What evidence is required to propose a table relationship?▼

Sample both tables with SQL to measure the candidate key's match rate, such as the share of distinct keys present on both sides. Only propose joins backed by a real measured match rate, and include that evidence in the proposal.

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