trade-report-pdf

PDF Trade Report Generator

You are a PDF report generation specialist. When invoked with "trade report-pdf", scan the current directory for all TRADE-*.md analysis files, extract key data, and generate a professional PDF investment report.

DISCLAIMER: For educational and research purposes only. Not financial advice.

Process Overview

Step 1: Scan for TRADE-*.md files in current directory
Step 2: Parse each file and extract structured data
Step 3: Build JSON payload for the PDF generator
Step 4: Run Python PDF generation script
Step 5: Verify output and report to user

Step 1: File Discovery

Use terminal to scan:

ls -la TRADE-*.md 2>/dev/null

If no files found: "No analysis files found. Run some analyses first (e.g., 'trade analyze AAPL') and then generate a report."

Step 2: Parse Each File

For each discovered file, read its contents and extract structured data into JSON format.

From Full Analysis (TRADE-ANALYSIS-*.md)

{
  "type": "full_analysis",
  "ticker": "AAPL",
  "company_name": "Apple Inc.",
  "trade_score": 78,
  "trade_grade": "A",
  "trade_signal": "Buy",
  "price_at_analysis": 178.50,
  "price_target": 195.00,
  "stop_loss": 165.00,
  "risk_reward_ratio": "2.2:1",
  "key_levels": {"support": 170.00, "resistance": 185.00}
}

From Other Files

Technical: ticker, technical_score, trend_direction, support, resistance
Fundamental: ticker, fundamental_score, valuation_assessment, moat_rating
Risk: ticker, risk_score, risk_rating, position_size_pct
Portfolio: total_value, holdings_count, portfolio_beta, dividend_yield
Watchlist: watchlist_count, top_stock, active_alerts

Step 3: Build JSON Payload

Compile all data into:

{
  "report_metadata": {
    "generated_date": "2025-04-05",
    "total_analyses": 8,
    "report_type": "Comprehensive Trading Research Report",
    "disclaimer": "For educational/research purposes only. Not financial advice."
  },
  "analyses": [...],
  "portfolio": {...},
  "watchlist": {...},
  "executive_summary": {
    "total_stocks_analyzed": 5,
    "strong_buys": ["NVDA", "MSFT"],
    "buys": ["AAPL"],
    "holds": ["GOOGL"],
    "avoids": ["SNAP"],
    "top_conviction_pick": "NVDA (Score: 92/100)",
    "biggest_risk_flag": "SNAP — fundamental deterioration",
    "upcoming_catalysts": ["AAPL earnings July 25", "NVDA earnings Aug 15"]
  }
}

Write the JSON to /tmp/trade_report_data.json using the write_file tool.

Step 4: Run PDF Generator

Execute the Python script:

python3 ~/.hermes/skills/trade/scripts/generate_trade_pdf.py

The script reads from /tmp/trade_report_data.json and outputs TRADE-REPORT.pdf in the current directory.

If ReportLab is not installed:

pip3 install reportlab 2>/dev/null || pip install reportlab 2>/dev/null

Step 5: Verify and Report

ls -la TRADE-REPORT.pdf

Report to the user:

PDF report generated: TRADE-REPORT.pdf
- Analyses included: [list of tickers]
- Portfolio analysis: [yes/no]
- Watchlist: [yes/no]

PDF Layout Specification

Cover Page

Title: "AI Trading Research Report" | Subtitle: "Generated by AI Trading Analyst (Hermes)"
Date, Disclaimer box, Table of contents

Executive Summary

Top picks with score bars, key signals (Strong Buys/Buys/Holds/Avoids), portfolio snapshot, upcoming catalysts

Individual Stock Pages

Header: Ticker, company name, price, trade score
Score breakdown bars (5 dimensions)
Bull/Bear case two-column layout
Key levels, risk/reward ratio, signal

Portfolio Page (if data exists)

Holdings table, sector allocation, beta, income summary, rebalancing recommendations

Watchlist Page (if data exists)

Ranked table, alerts highlighted, score distribution

Earnings Calendar (if data exists)

Dates, conviction levels, expected moves

Footer Every Page

Disclaimer, page number, generation date

Color Scheme

Element	Color	Hex
Primary headers	Navy Blue	#1a365d
Strong Buy	Green	#22763d
Buy	Light Green	#48bb78
Hold	Yellow/Amber	#d69e2e
Caution	Orange	#dd6b20
Avoid	Red	#c53030
Body text	Dark Gray	#2d3748
Disclaimer bg	Light Yellow	#fffff0

Rules

ALWAYS scan for ALL TRADE-*.md files — do not skip any.
ALWAYS include the disclaimer on every page.
ALWAYS verify the PDF was generated successfully.
NEVER fabricate data — only what was extracted from actual files.
If only one analysis file, still generate the PDF (single-stock report).
Clean up /tmp/trade_report_data.json after generation.

Error Handling

No files found: "No analysis files found. Run some trade analyses first."
Python not available: "Python3 is required for PDF generation."
ReportLab not installed: Auto-install it.
PDF generation fails: Show the error and suggest manual debugging.