Skill

research-company

From sundial-org-awesome-openclaw-skills-4

Generates professional PDF reports on B2B companies from URLs via web research, JSON structuring, and Python script. Covers profile, products, competitors, industry trends, and lead gen.

Python

automation

documentation

Install

npx claudepluginhub joshuarweaver/cascade-ai-ml-agents-misc-2 --plugin sundial-org-awesome-openclaw-skills-4

Tool Access

This skill uses the workspace's default tool permissions.

Preview

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

Supporting Assets

references/data-schema.mdscripts/generate_report.py

SKILL.md

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Stats

Stars586

Forks75

Last CommitFeb 1, 2026

Actions

View Source View Plugin View on GitHub View README

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:

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):

{
  "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

# 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:

[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