A skill for AI tools that generates deep, auditable equity research reports with traceable facts, replicable valuations, and auditable conclusions over nine chapters.

Stars

215

7-day growth

No data

Forks

33

Open issues

0

License

MIT

Last updated

2026-07-27

AI repository intelligence
FR-AI / ANALYSIS

Why it is worth attention

It brings institutional-grade research discipline to AI, emphasizing expectation gap analysis, forensic accounting quality checks, and multi-method valuation replication, far surpassing typical AI stock summaries.

Who it is for

  • Long-term equity investors
  • Fundamental analysts
  • Investment research teams
  • Investors requiring deep post-earnings reviews

Use cases

  • First-time in-depth research on a company to establish a complete baseline
  • Post-earnings analysis of expectation gaps, financial quality, and valuation changes
  • Creating auditable investment memoranda for long-term tracking
  • Cross-market comparisons among A-shares, HK stocks, and US stocks

Strengths

  • Nine-chapter report structure with rigorous flow
  • Built-in financial statement quality checks (accruals, M-Score, credibility grading)
  • Requires at least three cross-validated valuation methods with replicable scripts
  • 16 industry-specific appendixes tailored to different business models

Considerations

  • Not suitable for fast Q&A or high-frequency trading signals
  • Full functionality depends on web search and a Python environment
  • Steep learning curve for users unfamiliar with expectation gap and valuation discipline

README quick start

使用

Description

机构级个股投研报告 Agent Skill(九章结构 + 多方法估值交叉验证),适用于 Claude Code / Cowork / Codex 等 AI Agent 工具

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