AgentSkillsCN

Research Report Generator

研究报告生成器

SKILL.md

Research Report Generator Skill

Generates comprehensive financial research reports by consolidating data from multiple sources with structured formatting and actionable insights.

Usage

bash
claude-code skill research-report --symbol "AAPL" --type "investment"

Capabilities

  • Data Consolidation: Aggregates data from price history, financials, news, and technical indicators
  • Executive Summary: AI-generated concise summary of key findings
  • Structured Reports: Organized sections (Overview, Analysis, Risks, Valuation, Recommendation)
  • Markdown Formatting: Professional tables, headers, and formatting
  • Data Validation: Quality checks and source attribution
  • Multiple Report Types: Investment, Trading, Sector, and ESG reports
  • Actionable Insights: Specific recommendations with risk levels

Parameters

ParameterRequiredDescriptionExamples
symbolYesStock ticker symbolAAPL, MSFT, GOOGL
typeNoReport type (default: investment)investment, trading, sector, esg
periodNoAnalysis period (default: 1y)3m, 6m, 1y, 3y
includeNewsNoInclude news analysis (default: true)true, false
includeTechnicalNoInclude technical analysis (default: true)true, false

Examples

bash
# Generate investment research report
claude-code skill research-report --symbol "AAPL" --type "investment"

# Generate short-term trading report
claude-code skill research-report --symbol "TSLA" --type "trading" --period "3m"

# Generate sector comparison report
claude-code skill research-report --symbol "MSFT" --type "sector"

Report Structure

Investment Research Report

code
# Investment Research Report: Apple Inc. (AAPL)

**Date:** January 15, 2025
**Analyst:** AI Research System
**Recommendation:** BUY
**Price Target:** $210.00

---

## Executive Summary

[2-3 paragraph summary of key findings, recommendation, and investment thesis]

---

## Company Overview

- Business Description
- Key Products/Services
- Market Position
- Competitive Landscape

---

## Financial Analysis

### Revenue & Earnings
- Revenue trends (3-year CAGR)
- Margin analysis
- Earnings quality

### Balance Sheet
- Cash position
- Debt levels
- Return on capital

### Cash Flow
- Operating cash flow
- Free cash flow
- Capital allocation

---

## Valuation

- P/E Ratio vs Peers
- DCF Analysis
- Comparable Companies
- 52-Week Range Context

---

## Growth Drivers

1. Product Cycle
2. Market Expansion
3. M&A Opportunities
4. Margin Expansion

---

## Risk Factors

1. Competition Risks
2. Regulatory Risks
3. Macro Risks
4. Company-Specific Risks

---

## Technical Analysis

- Trend Status
- Support/Resistance Levels
- Moving Average Analysis
- Momentum Indicators

---

## News & Sentiment

- Recent Headlines
- Sentiment Analysis
- Key Events

---

## Investment Recommendation

**Verdict:** BUY
**Confidence:** HIGH
**Time Horizon:** 12 months
**Entry Zone:** $175-$185
**Stop Loss:** $160
**Price Target:** $210

**Rationale:** [Detailed recommendation reasoning]

---

## Sources

- Finnhub API
- Alpha Vantage API
- Company Filings
- Market Data

Report Types

Investment Report

  • Time Horizon: 12-24 months
  • Focus: Fundamentals, valuation, long-term growth
  • Audience: Long-term investors, portfolio managers
  • Key Metrics: P/E, FCF, ROIC, CAGR

Trading Report

  • Time Horizon: Days to weeks
  • Focus: Technical patterns, momentum, catalysts
  • Audience: Active traders, hedge funds
  • Key Metrics: RSI, MACD, Volume, Support/Resistance

Sector Report

  • Scope: Company within industry context
  • Focus: Relative performance, sector trends
  • Audience: Sector analysts, thematic investors
  • Key Metrics: Relative strength, sector multiples

ESG Report

  • Focus: Environmental, Social, Governance
  • Metrics: Carbon footprint, diversity, policies
  • Growing: Sustainable investing demand

Output

Reports are generated as Markdown with:

  • Proper heading hierarchy (H1-H4)
  • Data tables with alignment
  • Bullet points for readability
  • Bold for emphasis
  • Code blocks for data
  • Source attribution footnotes

Notes

  • Reports use real-time data from MCP APIs
  • AI generates narrative sections from structured data
  • All claims include source attribution
  • Confidence levels indicated based on data quality
  • Reports include specific actionability (entry/exit points, targets, stops)