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cb-analytics-schema

Discover Couchbase Analytics dataverses, datasets, and infer document field schemas.

4|1|Updated May 28, 2026
Search Tags:#analytics#schema#data dictionary#dataset#dataverse#couchbase#sql++
One-click install
npx skills add https://github.com/celticht32/Couchbase-Skills-for-Claude.ai --skill cb-analytics-schema
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cb-analytics-schema
Source: https://github.com/celticht32/Couchbase-Skills-for-Claude.ai/tree/main/skills/couchbase-analytics/cb-analytics-schema
Command: npx skills add https://github.com/celticht32/Couchbase-Skills-for-Claude.ai --skill cb-analytics-schema

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you quickly understand what data exists in Couchbase Analytics without manually inspecting every dataset, making schema discovery, documentation, and exploration much faster.

Core Features & Use Cases

  • Dataverse Discovery: List available dataverses in a cluster so you can find where analytics data lives.
  • Dataset Enumeration: Inspect datasets within a dataverse to identify the right source for analysis or reporting.
  • Schema Inference: Sample documents to infer field names, types, presence rates, and heterogeneous shapes for data dictionaries and downstream query design.
  • Use Case: A data analyst can discover a new Analytics dataset, infer its structure, and document optional fields before writing SQL++ queries or building a dashboard.

Quick Start

Ask the skill to inspect a Couchbase Analytics dataset schema and summarize the fields, types, and optional attributes.

Frequently Asked Questions about cb-analytics-schema

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

FAQPage Schema
How do I discover the schema of a Couchbase Analytics dataset?▼

Schema inference for Couchbase Analytics works by sampling documents within a dataset. It identifies field names, data types, presence rates, and heterogeneous document shapes to build a comprehensive data dictionary for exploration.

Can I infer field types and presence rates for heterogeneous Couchbase documents?▼

Yes, inferring field types and presence rates for heterogeneous Couchbase documents is possible. The process samples documents to report field presence, identify types, and map heterogeneous document shapes for data dictionary creation.

What is the best way to enumerate datasets within a Couchbase dataverse?▼

Enumerating datasets within a Couchbase dataverse involves inspecting the dataverse to identify available data sources. This ensures you select the correct dataset for analytics exploration and accurate schema documentation.

Do I need to inspect every dataset manually to build a Couchbase data dictionary?▼

No, manual inspection of every dataset is unnecessary for building a Couchbase data dictionary. Automated schema discovery samples documents to report field presence, types, and heterogeneous shapes, accelerating documentation and exploration.

How does schema inspection help with SQL++ query planning in Couchbase?▼

Schema inspection aids SQL++ query planning by revealing dataset structure, field types, and optional attributes. This structural visibility ensures accurate query design and effective analytics exploration across Couchbase dataverses.

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