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Comprehensive industry research skill providing methodologies, frameworks, and best practices for analyzing industry trends, key companies, market dynamics, and industry-specific developments across consumer, tech, healthcare, and finance sectors
npx skill4agent add rkreddyp/investrecipes industry-researchoutputs/
└── <agent_name>/
└── <customer_name>/
├── reports/ # Final markdown research reports
├── scripts/ # Generated research code
├── raw/ # JSON/CSV data files
└── screenshots/ # PNG screenshots of sources## [Industry] Research Report
**Generated:** [Date/Time]
**Research Period:** [Date range]
**Sources Analyzed:** [List of sources]
---
### Executive Summary
[2-3 paragraph overview of key findings]
---
### Industry Trends
[Current trends with analysis and sources]
---
### Key Companies & Market Leaders
[Top companies with market position and analysis]
---
### Market Dynamics
[Market size, growth rates, key metrics with sources]
---
### Recent Developments
[Industry news and events with dates and sources]
---
### Future Outlook
[Emerging trends, predictions, and opportunities]
---
### Source Attribution
[List of all sources and URLs used]import asyncio
from playwright.async_api import async_playwright
async def research_industry_trends(industry_sources):
"""
Research industry trends from multiple sources.
Args:
industry_sources (list): List of URLs to research
Returns:
dict: Research findings organized by source
"""
findings = {}
async with async_playwright() as p:
browser = await p.chromium.launch()
page = await browser.new_page(viewport={"width": 1920, "height": 1080})
for source_url in industry_sources:
try:
# Navigate and capture
await page.goto(source_url, wait_until="domcontentloaded", timeout=120000)
await page.screenshot(path=f"screenshot_{source_url.replace('/', '_')}.png", full_page=True)
# Extract data (implement based on page structure)
# ... extraction logic ...
findings[source_url] = extracted_data
except Exception as e:
print(f"Error researching {source_url}: {e}")
await browser.close()
return findingsasync def extract_market_metrics(page, selector_mapping):
"""
Extract market metrics from a financial data page.
Args:
page: Playwright page object
selector_mapping (dict): Mapping of metric names to CSS selectors
Returns:
dict: Extracted metrics
"""
metrics = {}
for metric_name, selector in selector_mapping.items():
try:
element = await page.query_selector(selector)
if element:
text = await element.inner_text()
metrics[metric_name] = text.strip()
except Exception as e:
print(f"Error extracting {metric_name}: {e}")
return metricsconsumer_researcher.mdtech_researcher.mdhealthcare_researcher.mdfinance_researcher.md