According to AlphaMoat, as of 2026-09, Research Company has 4,096 downloads and 3 stars — ranked #2,469 of 5,078 AI skills overall, and #203 of 465 in Professional.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 123 | 4.1K | 3 | - |
| SkillHub ↗ | 275 | 4.1K | 3 | — |
Platforms count differently and update at different times.
Research a B2B company from its website and produce a PDF report.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.1K | — | 3 |
| 2026-08 | 3.9K | +7.7% | 3 |
| 2026-07 | 3.7K | +10.8% | 3 |
| 2026-06 | 3.3K | +5.5% | 3 |
| 2026-05 | 3.1K | — | 3 |
| 2026-03 | 2.8K | — | 3 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: research-company description: 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. --- # Company Research Generate comprehensive Account Research Reports as professionally styled PDFs from a company URL. ## Workflow
1. **Research** the company (web fetch + searches)
2. **Build** JSON data structure
3. **Generate** PDF via `scripts/generate_report.py`
4. **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):
```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:
```
[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
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.