Company Research

Generate comprehensive Account Research Reports as professionally styled PDFs from a company URL.

Workflow

•Research the company (web fetch + searches)
•Build JSON data structure
•Generate PDF via scripts/generate_report.py
•Deliver PDF to user

Phase 1: Research (Parallel)

Execute these searches concurrently to minimize context usage:

code

WebFetch: [company URL]
WebSearch: "[company name] funding news 2024"
WebSearch: "[company name] competitors market"
WebSearch: "[company name] CEO founder leadership"

Extract from website: company name, industry, HQ, founded, leadership, products/services, pricing model, target customers, case studies, testimonials, recent news.

Phase 2: Build Data Structure

Create JSON matching this schema (see references/data-schema.md for full spec):

json

{
  "company_name": "...",
  "source_url": "...",
  "report_date": "January 20, 2026",
  "executive_summary": "3-5 sentences...",
  "profile": { "name": "...", "industry": "...", ... },
  "products": { "offerings": [...], "differentiators": [...] },
  "target_market": { "segments": "...", "verticals": [...] },
  "use_cases": [{ "title": "...", "description": "..." }],
  "competitors": [{ "name": "...", "strengths": "...", "differentiation": "..." }],
  "industry": { "trends": [...], "opportunities": [...], "challenges": [...] },
  "developments": [{ "date": "...", "title": "...", "description": "..." }],
  "lead_gen": { "keywords": {...}, "outreach_angles": [...] },
  "info_gaps": ["..."]
}

Phase 3: Generate PDF

bash

# Install if needed
pip install reportlab

# Save JSON to temp file
cat > /tmp/research_data.json << 'EOF'
{...your JSON data...}
EOF

# Generate PDF
python3 scripts/generate_report.py /tmp/research_data.json /path/to/output/report.pdf

Phase 4: Deliver

Save PDF to workspace folder and provide download link:

code

[Download Company Research Report](computer:///sessions/.../report.pdf)

Quality Standards

•Accuracy: Base claims on observable evidence; cite sources
•Specificity: Include product names, metrics, customer examples
•Completeness: Note gaps as "Not publicly available"
•No fabrication: Never invent information

Resources

•scripts/generate_report.py - PDF generator (uses reportlab)
•references/data-schema.md - Full JSON schema with examples