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insight_nl2code

Execute user-provided pandas code in a secure sandbox with serialized results.

Updated Aug 27, 2026
Search Tags:#insights#pandas#data-analysis#sandbox#custom-code#nl2code
One-click install
npx skills add https://github.com/huangxn27/broadband-agent-demo --skill insight-nl2code
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: insight_nl2code
Source: https://github.com/huangxn27/broadband-agent-demo/tree/main/backend/skills/insight_nl2code
Command: npx skills add https://github.com/huangxn27/broadband-agent-demo --skill insight-nl2code

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ce_insight_core, json_repair, and includes scripts (resource) and references (resource) components.

What problem does it solve?

NL2Code sandbox enables executing user-provided pandas code within a secure sandbox to perform bespoke analyses that are not covered by the standard 12 insight functions.

Core Features & Use Cases

  • Sandbox execution of pandas code with safety constraints and structured output
  • Supports advanced queries like Top N, custom multi-column comparisons, and derived metrics
  • Returns serialized results in a consistent format for downstream tooling or dashboards

Quick Start

Provide a payload with code and query_config to the NL2Code sandbox and observe the structured result.

Frequently Asked Questions about insight_nl2code

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

FAQPage Schema
How do I run custom pandas code for data analysis beyond standard insights?▼

To run custom pandas code for data analysis, you can execute user-provided scripts in a secure sandbox. This enables bespoke data transformations like Top N selections and multi-column comparisons beyond built-in insight functions.

Can I perform Top N selections and multi-column comparisons using pandas safely?▼

Yes, you can perform Top N selections and multi-column comparisons safely. The sandbox environment enforces restricted execution with explicit input and output contracts, ensuring custom pandas operations remain reproducible.

How do I execute bespoke data transformations in a restricted pandas environment?▼

You execute bespoke data transformations by providing a payload with custom code and a query configuration. The sandbox processes the pandas operations and returns serialized results in a consistent format for downstream tooling.

Does the custom pandas sandbox support structured output for downstream dashboards?▼

Yes, the custom pandas sandbox supports structured output for downstream dashboards. It returns serialized results in a consistent format, ensuring that outputs from your bespoke data analysis are readily available for integration.

What are the limitations of using a sandbox for custom pandas data analysis?▼

The sandbox approach for custom pandas data analysis enforces a restricted environment with safety constraints. While it supports advanced queries, operations must adhere to explicit input and output contracts to ensure execution safety and reproducibility.

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