explore

Name: explore
Availability: InStock
Author: Platyplus

Query and aggregate structured data from Cairn collections into tables and charts.

Updated Jul 23, 2026

Search Tags:#analytics #data #reporting #visualization #query #cairn

Ready to run

npx skills add https://github.com/platyplus/cairn-plugin --skill explore-platyplus

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: explore
Source: https://github.com/platyplus/cairn-plugin/tree/main/cairn/skills/explore
Command: npx skills add https://github.com/platyplus/cairn-plugin --skill explore-platyplus

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the difficulty of querying and visualizing complex, schema-driven data without needing to write manual SQL or complex database code.

Core Features & Use Cases

Data Querying: Retrieve specific records from collections using natural language filters.
Aggregation & Visualization: Automatically generate counts, trends, and charts (bar, line, scatter, choropleth) based on your data structure.
Use Case: A humanitarian field team can ask to see a trend of cholera cases by month or a map of facility locations to make rapid, data-informed decisions.

Quick Start

Use the explore skill to show me a bar chart of the total number of cases broken down by facility type.

Frequently Asked Questions about explore

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

FAQPage Schema

How do I visualize structured data collections without writing SQL?▼

You can visualize structured data by querying Cairn collections using natural language filters. The system automatically aggregates records and generates tables, bar charts, line charts, scatter plots, and choropleth maps based on your data's schema.

Can I generate time-series charts from raw collection data?▼

Yes, generating time-series charts is supported for raw collection data. The system queries and aggregates structured records, allowing you to group data by time intervals to visualize trends and generate actionable charts.

Does data visualization require schema-aware field selection?▼

Yes, accurate data visualization requires schema-aware field selection. The system relies on precise CEL-based filtering and your data's structure to ensure correct aggregation, grouping, and representation across generated charts and maps.

What is the best way to create a choropleth map from aggregated data?▼

The best way to create a choropleth map is by querying structured Cairn collections with natural language filters. The system automatically aggregates the geographical data and generates the map based on the underlying schema.

How do I filter records when querying structured collections?▼

You filter records by applying precise CEL-based filtering when querying structured collections. This ensures accurate data retrieval and aggregation before generating tables, charts, or maps for visualization.