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Junmo Enterprise Analysis Framework

Professional Updated 2026.08.30

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About this skill

Problem

Public earnings reports, investor-relations Q&A, and third-party commentary are scattered. Reading a single income statement can be misleading when nonrecurring items, stale data, or management guidance dominate the picture. Junmo addresses this by turning equity research into a repeatable fundamentals workflow that starts from verified facts rather than treating broker forecasts as conclusions.

How It Works

The framework follows a question-driven, data-validated, neutral-judgment loop. It typically covers company overview, business mix, growth drivers, financial quality, cash flow, balance sheet, valuation, dividends, governance, peer comparison, bull-bear debate, and action recommendations. Key steps include:
- routing data requests to relevant sources based on exchange and ticker;
- cross-checking revenue, profit, cash flow, dividends, and shareholder transactions across multiple sources;
- explicitly marking [management statement], [industry forecast], and [analyst forecast];
- producing standalone HTML pages for latest-report interpretation, interim forecasting, or dividend-sustainability analysis when triggered;
- using independent data-verification agent and process-audit agent checks before data ingestion and before deployment to verify completeness, timeliness, and compliance.

Boundary

This is a research and reporting framework, not a trading signal system, real-time market data feed, or regulated investment advice. Public data should still be manually confirmed for reporting period, dividend announcements, and transaction documents before use.

Use Cases

  • Analyze an A-share listed company by producing a 21-section report covering overview, business mix, profit, cash flow, and valuation.
  • Interpret the latest half-year or annual report and generate a standalone HTML deep-dive with KPIs, risks, dividends, and actions.
  • Assess dividend sustainability by checking parent-company debt pressure, listed-company cash capacity, and historical payout patterns.
  • Forecast interim results before disclosure using announced operating data, three scenarios, explicit assumptions, and catalyst timing.

Best For

  • Equity researchers who need to turn company research into structured deep-dive reports.
  • Investment analysts who verify earnings, investor Q&A, and external risk signals.
  • Private investors who track dividend sustainability, pledge ratios, and parent-company debt pressure.
  • Research team members who cross-check financial forecasts and valuation assumptions across sources.