Job URL Analyzer MCP Server

"""Generate markdown reports from company analysis data.""" from datetime import datetime from typing import Dict, Any, List import structlog logger = structlog.get_logger(__name__) class ReportGenerator: """Generates comprehensive markdown reports from analysis data.""" async def generate_report( self, company_data: Dict[str, Any], completeness_score: float, confidence_score: float, enrichment_sources: List[str], enrichment_errors: List[str], ) -> str: """Generate a comprehensive markdown report.""" report_sections = [] # Header company_name = company_data.get("name", "Unknown Company") report_sections.append(f"# {company_name} - Company Analysis Report") report_sections.append(f"*Generated on {datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S')} UTC*") report_sections.append("") # Executive Summary report_sections.append("## Executive Summary") summary = self._generate_executive_summary(company_data) report_sections.append(summary) report_sections.append("") # Company Overview if any(company_data.get(field) for field in ["description", "industry", "founded_year"]): report_sections.append("## Company Overview") if company_data.get("description"): report_sections.append(f"**Description:** {company_data['description']}") report_sections.append("") overview_items = [] if company_data.get("industry"): overview_items.append(f"**Industry:** {company_data['industry']}") if company_data.get("founded_year"): overview_items.append(f"**Founded:** {company_data['founded_year']}") if company_data.get("website"): overview_items.append(f"**Website:** {company_data['website']}") if overview_items: report_sections.extend(overview_items) report_sections.append("") # Size and Funding if any(company_data.get(field) for field in ["employee_count", "employee_count_range", "funding_stage", "total_funding"]): report_sections.append("## Size & Funding") if company_data.get("employee_count"): report_sections.append(f"**Employee Count:** {company_data['employee_count']:,}") elif company_data.get("employee_count_range"): report_sections.append(f"**Employee Range:** {company_data['employee_count_range']}") if company_data.get("funding_stage"): report_sections.append(f"**Funding Stage:** {company_data['funding_stage']}") if company_data.get("total_funding"): report_sections.append(f"**Total Funding:** ${company_data['total_funding']:.1f}M") report_sections.append("") # Location if company_data.get("headquarters") or company_data.get("locations"): report_sections.append("## Location") if company_data.get("headquarters"): report_sections.append(f"**Headquarters:** {company_data['headquarters']}") if company_data.get("locations") and len(company_data["locations"]) > 0: report_sections.append("**Other Locations:**") for location in company_data["locations"]: report_sections.append(f"- {location}") report_sections.append("") # Technology & Culture tech_culture_added = False if company_data.get("tech_stack") and len(company_data["tech_stack"]) > 0: if not tech_culture_added: report_sections.append("## Technology & Culture") tech_culture_added = True report_sections.append("**Technology Stack:**") for tech in company_data["tech_stack"]: report_sections.append(f"- {tech}") report_sections.append("") if company_data.get("benefits") and len(company_data["benefits"]) > 0: if not tech_culture_added: report_sections.append("## Technology & Culture") tech_culture_added = True report_sections.append("**Benefits & Perks:**") for benefit in company_data["benefits"]: report_sections.append(f"- {benefit}") report_sections.append("") if company_data.get("culture_keywords") and len(company_data["culture_keywords"]) > 0: if not tech_culture_added: report_sections.append("## Technology & Culture") tech_culture_added = True report_sections.append("**Culture Keywords:**") culture_tags = ", ".join(company_data["culture_keywords"]) report_sections.append(culture_tags) report_sections.append("") # Social Presence if company_data.get("linkedin_url") or company_data.get("twitter_url"): report_sections.append("## Social Presence") if company_data.get("linkedin_url"): report_sections.append(f"**LinkedIn:** {company_data['linkedin_url']}") if company_data.get("twitter_url"): report_sections.append(f"**Twitter:** {company_data['twitter_url']}") report_sections.append("") # Analysis Quality report_sections.append("## Analysis Quality") report_sections.append(f"**Data Completeness:** {completeness_score:.1%}") report_sections.append(f"**Confidence Score:** {confidence_score:.1%}") if enrichment_sources: sources_text = ", ".join(enrichment_sources) report_sections.append(f"**Enrichment Sources:** {sources_text}") if enrichment_errors: report_sections.append("**Enrichment Issues:**") for error in enrichment_errors: report_sections.append(f"- {error}") report_sections.append("") # Footer report_sections.append("---") report_sections.append("*This report was generated automatically by Job URL Analyzer. Data accuracy may vary.*") return "\n".join(report_sections) def _generate_executive_summary(self, company_data: Dict[str, Any]) -> str: """Generate an executive summary paragraph.""" summary_parts = [] company_name = company_data.get("name", "This company") # Basic description if company_data.get("description"): summary_parts.append(company_data["description"]) else: summary_parts.append(f"{company_name} is a company") # Industry and stage details = [] if company_data.get("industry"): details.append(f"in the {company_data['industry'].lower()} industry") if company_data.get("founded_year"): current_year = datetime.now().year age = current_year - company_data["founded_year"] details.append(f"founded {age} years ago ({company_data['founded_year']})") if company_data.get("headquarters"): details.append(f"headquartered in {company_data['headquarters']}") if details: summary_parts.append(" ".join(details)) # Size information if company_data.get("employee_count"): summary_parts.append(f"The company has approximately {company_data['employee_count']:,} employees") elif company_data.get("employee_count_range"): summary_parts.append(f"The company has {company_data['employee_count_range']} employees") # Funding information if company_data.get("funding_stage") and company_data.get("total_funding"): summary_parts.append(f"and has raised ${company_data['total_funding']:.1f}M in {company_data['funding_stage'].lower()} funding") elif company_data.get("funding_stage"): summary_parts.append(f"and is at the {company_data['funding_stage'].lower()} stage") elif company_data.get("total_funding"): summary_parts.append(f"and has raised ${company_data['total_funding']:.1f}M in funding") return ". ".join(summary_parts) + "."