ask-q6-business-model

Analyze multi-year mainbz data to assess business model stability and concentration risks.

2|1|Updated Apr 17, 2026
One-click install
npx skills add https://github.com/shadowinlife/nano_quant_skills --skill ask-q6-business-model
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ask-q6-business-model
Source: https://github.com/shadowinlife/nano_quant_skills/tree/main/2min-company-analysis/ask-q6-business-model
Command: npx skills add https://github.com/shadowinlife/nano_quant_skills --skill ask-q6-business-model

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill helps analysts quickly assess the stability and diversification of a company's business model by aggregating multi-year main business segment data (from annual reports and company disclosures) to identify concentration risks and track evolution over time.

Core Features & Use Cases

  • Multi-year mainbz analysis to measure top-segment share, segment changes, and the appearance of new business lines.
  • Evidence harness that combines annual reports and segment disclosures to support a ready/partial assessment with traceable sources.
  • Use Case: evaluate whether revenue depends on a single product or client, or whether a second curve is emerging, to inform investment or strategic decisions.

Quick Start

Run the Q6 business-model analysis script with a stock code to generate an evidence-backed readiness assessment.

Frequently Asked Questions about ask-q6-business-model

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

FAQPage Schema
How do I assess business model stability using multi-year mainbz data?

Evaluating business model stability involves aggregating multi-year mainbz data from annual reports to detect product or client concentration, track segment changes, and flag new revenue items. This produces a structured assessment with readiness status and traceable evidence sources.

What is the best way to track segment changes across multiple years in annual reports?

Tracking segment changes across multiple years involves applying analysis across stock codes to identify top-segment share variations and the emergence of new business lines. This combines annual report disclosures to support an assessment with traceable evidence sources.

Can I detect product or client concentration risks from company disclosures?

Yes, detecting product or client concentration risks is achieved by analyzing multi-year mainbz data to measure top-segment share and evaluate revenue dependency. This combines annual reports and segment disclosures to produce an evidence-backed assessment for decision making.

How do I identify if a second revenue curve is emerging from historical business segments?

Identifying an emerging second revenue curve involves tracking the appearance of new business lines and segment changes across multiple years of mainbz data. This flags new revenue items and produces a structured assessment with rating and traceable evidence sources.

Does this stock analysis approach require specific dependencies to run?

No, this stock analysis approach requires no external dependencies to run. The script operates independently across stock codes, aggregating evidence from annual reports and segment disclosures to produce a structured readiness status for decision making.