data-intel

Aggregate and synthesize cross-system data from PostHog, Airtable, Slack, Customer.io, and n8n.

6|Updated Mar 26, 2026

Search Tags:#data #insights #Slack #cross-system #analyze #PostHog #Airtable

Ready to run

npx skills add https://github.com/thensls/nsls-builder-toolkit --skill data-intel

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-intel
Source: https://github.com/thensls/nsls-builder-toolkit/tree/main/skills/data-intel
Command: npx skills add https://github.com/thensls/nsls-builder-toolkit --skill data-intel

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Siloed data across PostHog, Airtable, Slack, Customer.io, n8n, and other connected tools prevents teams from seeing the full story. Data-intel provides cross-system synthesis to deliver both macro trends and micro context for informed decision-making.

Core Features & Use Cases

Cross-system querying and synthesis across the major NSLS data sources.
Macro insights with concrete micro details, enabling evidence-backed decisions.
Use cases include engagement analytics, campaign performance, product health, and operational health.

Quick Start

Ask data-intel to summarize the last 30 days across all connected systems.

Frequently Asked Questions about data-intel

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

FAQPage Schema

How do I analyze cross-system data from PostHog, Airtable, and Slack in one place?▼

Cross-system data analysis aggregates and synthesizes information from PostHog, Airtable, Slack, Customer.io, and n8n into unified insights. You can query users, engagement, campaigns, workflows, and operational health across connected sources to get macro trends and micro details.

What is cross-system data synthesis and when do I need it?▼

Cross-system data synthesis resolves siloed data across tools like PostHog, Airtable, and Slack by combining them into a single view. You need it when teams require both macro trends and micro context to make evidence-backed decisions about engagement or operational health.

How do I connect my data sources to start querying cross-system insights?▼

To start querying cross-system insights, you must establish explicit connections to your data sources using the /connect command. This authorizes the tool to access PostHog, Airtable, Slack, Customer.io, and n8n data for aggregation and synthesis.

Does cross-system data analysis work with a strict privacy and permission model?▼

Cross-system data analysis enforces strict privacy and safety through a three-tier permission model and PII redaction rules. This ensures that sensitive information is protected while you query engagement analytics, campaign performance, and operational health across connected systems.

What's the best way to summarize multi-system data for the last 30 days?▼

The best way to summarize multi-system data is to request a synthesis across all connected sources for the last 30 days. This aggregates PostHog, Airtable, Slack, Customer.io, and n8n data to deliver macro trends and humanizing micro details.