Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
B2B company research producing professional PDF reports. Use when asked to research a company, analyze a business, create an account profile, or generate market intelligence from a company URL. Outputs a beautifully formatted, downloadable PDF report.
B2B company research producing professional PDF reports. Use when asked to research a company, analyze a business, create an account profile, or generate market intelligence from a company URL. Outputs a beautifully formatted, downloadable PDF report.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Generate comprehensive Account Research Reports as professionally styled PDFs from a company URL.
Research the company (web fetch + searches) Build JSON data structure Generate PDF via scripts/generate_report.py Deliver PDF to user
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.
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": ["..."] }
# 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
Save PDF to workspace folder and provide download link: [Download Company Research Report](computer:///sessions/.../report.pdf)
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
scripts/generate_report.py - PDF generator (uses reportlab) references/data-schema.md - Full JSON schema with examples
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.