investment-memo-writer

Orchestrates end-to-end investment memo generation from market and company data.

6|1|Updated Apr 2, 2026
One-click install
npx skills add https://github.com/kouko/monkey-skills --skill investment-memo-writer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: investment-memo-writer
Source: https://github.com/kouko/monkey-skills/tree/main/investing-toolkit/skills/investment-memo-writer
Command: npx skills add https://github.com/kouko/monkey-skills --skill investment-memo-writer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, yfinance, pandas, and includes scripts (resource) components.

What problem does it solve?

Orchestrates and automates the manual, error-prone process of collecting market and company data, building macro context, and running structured equity research workflows so analysts can produce a complete investment memo reliably and repeatably.

Core Features & Use Cases

  • Data assembly: Fetches price history and company info via yfinance, macro series via FRED, and Taiwan-specific datasets via FinMind when applicable.
  • Regime context: Integrates macro-regime-snapshot outputs (IC/GIP/yield curve) to ground thesis and scenarios.
  • Analysis orchestration & gates: Delegates analysis to domain-teams:investing-team for the Deep Equity Research Memo workflow and captures MUST/SHOULD/MAY gate verdicts and validation.
  • Optional formatting: Hands the raw memo to docs-team for polished, PDF-ready output when requested.
  • Use case: Produce a full deep equity research memo for a US or Taiwan ticker, including data freshness, gate verdicts, and Taiwan-specific diagnostics when relevant.

Quick Start

Run the investment-memo-writer for ticker AAPL with scope deep to fetch market and macro data, run the investing-team workflow, and return the full memo with gate verdicts and data freshness.

Frequently Asked Questions about investment-memo-writer

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

FAQPage Schema
How do I automate equity research and generate an investment memo from raw market data?

Automating equity research to generate an investment memo involves orchestrating end-to-end data collection from yfinance and FRED, building macro context, and running structured analysis workflows. This skill coordinates those fetches and forwards structured fixtures to produce a complete research memo with gate verdicts.

Can I use yfinance and FRED data for Taiwan market equity research?

Yes, yfinance and FRED data can be used for Taiwan market equity research. The workflow also integrates FinMind to fetch Taiwan-specific datasets, ensuring comprehensive coverage for single-ticker analyses in both US and Taiwan markets.

What is the best way to include macro-regime context in a deep equity research memo?

Including macro-regime context in a deep equity research memo requires integrating macro-regime-snapshot outputs like IC/GIP and yield curve data. This skill grounds your investment thesis and scenarios by forwarding these macro fixtures alongside company data to the analysis team.

Does this investment memo workflow support MUST, SHOULD, and MAY validation gates?

Yes, this investment memo workflow supports MUST, SHOULD, and MAY validation gates. It delegates analysis to a domain investing team, captures these specific gate verdicts, and reports data freshness and validation results within the final structured research memo.

How do I format a generated equity research memo into a PDF-ready document?

Formatting a generated equity research memo into a PDF-ready document is supported through an optional docs-team integration. After the raw memo is generated and validated, the workflow can hand off the output to the docs-team for polished formatting.

Do I need to install pandas and requests to run the investment memo generation workflow?

Yes, you need to install pandas and requests to run the investment memo generation workflow. These dependencies are required alongside yfinance to properly fetch market data, structure the fixtures, and forward them between the data-fetcher and analysis components.