bsl-query-expert

Name: bsl-query-expert
Availability: InStock
Author: boringdata

Queries BSL semantic models and displays results with charts.

476|44|Updated Jun 13, 2025

Search Tags:#visualization #query #data-analysis #semantic-models #model-discovery #ibis

Ready to run

npx skills add https://github.com/boringdata/boring-semantic-layer --skill bsl-query-expert

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bsl-query-expert
Source: https://github.com/boringdata/boring-semantic-layer/tree/main/docs/md/skills/claude-code/bsl-query-expert
Command: npx skills add https://github.com/boringdata/boring-semantic-layer --skill bsl-query-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Discover and query BSL semantic models without writing low-level code, enabling rapid insight from semantic tables.

Core Features & Use Cases

Discover models with list_models() and inspect schemas with get_model(name).
Learn the query syntax via get_documentation("query-methods") and execute queries with query_model(query).
Automatically display results and charts, enabling end-to-end exploration and quick summaries.

Quick Start

Ask it to list models, inspect a model's schema, and run a sample query to see results.

Frequently Asked Questions about bsl-query-expert

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

FAQPage Schema

How do I query semantic models without writing low-level code?▼

You can query BSL semantic models by using the query_model function to execute queries directly. It enforces exact field names and proper prefix usage for joined columns, returning results with auto-displayed charts for rapid insight.

What is the process for discovering and inspecting data schemas for analysis?▼

Schema discovery for data analysis involves listing available models and then retrieving the specific schema for a target model. You can use list_models to discover models and get_model to inspect schemas before running exploratory queries.

How do I ensure correct syntax when querying joined columns in semantic models?▼

Querying joined columns in semantic models requires using proper prefixes for the joined fields and enforcing exact field names. You can retrieve detailed syntax rules and constraints by accessing the query-methods documentation before executing your query.

Can I automatically visualize query results during exploratory data analysis?▼

Yes, automatically visualizing query results during exploratory data analysis is supported. When you execute a query using the model query methods, the results are returned with auto-displayed charts to enable end-to-end interactive exploration and quick summaries.

What access is required to perform model discovery and guided querying?▼

Performing model discovery and guided querying requires access to specific functions including list_models, get_model, get_documentation, and query_model. This access enables you to discover models, inspect schemas, learn syntax, and execute queries across interactive sessions.

Are there limitations when using exact field names for data visualization queries?▼

The main limitation when querying for data visualization is that the system strictly enforces exact field names and proper prefix usage for joined columns. You must verify schema details and query syntax beforehand to avoid errors during model querying.