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Careerproof

Career and workforce intelligence built on a deep HR ontology — skill taxonomies, role definitions and responsibilities, compensation and incentive structures, learning and development pathways, sourcing strategies, and role/skill evolution mapping. This structured foundation, combined with a RAG knowledge base curated from 50+ premium sources (HBR, McKinsey, BCG, Gartner, Forrester) and updated 3x daily with live web research, powers 6 guided skills and 42 MCP tools for two audiences: working professionals getting personalized career intelligence (CV optimization, salary benchmarking, career strategy), and HR/TA teams running structured talent evaluation, candidate shortlisting, compensation analysis, and consulting-grade workforce research reports. Example Use Cases (for HR/TA teams): 1. Custom Evaluation Models — Train CareerProof on your organization's existing assessment rubrics, scorecards, and evaluation criteria to build custom eval models that evaluate candidates through your specific lens. Upload your competency frameworks and historical assessments, then run inference on new candidates — scored and ranked exactly how your team would, at scale. 2. Candidate Evaluation & Shortlisting — Set up a hiring context with company profile and job description, upload candidate CVs, then batch-rank them with GEM competency scoring and JD-FIT matching. Apply your custom eval models for organization-specific scoring, or deep-dive any candidate with a 360-degree evaluation including tailored interview questions derived from skill taxonomy analysis. 3. Workforce Research Reports — Generate consulting-grade PDF reports across 16 types (salary benchmarking, skills gap analysis, org design, DEI assessment, succession planning, sourcing strategy, and more). Each report is grounded in real-time market data from premium sources and structured around HR ontology — role definitions, compensation structures, L&D pathways, and skill evolution mapping. 4. Compensation & Incentive Benchmarking — Get market-calibrated salary and total compensation intelligence for any role, location, and industry. Analysis is structured around compensation and incentive frameworks from the HR ontology, enriched with live web research and curated knowledge base data covering base salary, equity, bonuses, and benefits. Example Use Cases (for the working professional or career coach): 1. Career Intelligence Chat (Hyper-Personalized) — Ask career strategy questions and get hyper-personalized responses that fuse your CV context with deep insights from the career and workforce RAG knowledge base. Salary benchmarks calibrated to your function and location, industry disruption analysis mapped to your skill profile, and career pivot recommendations grounded in role evolution data — not surface-level answers, but intelligence drawn from the same sources that inform executive strategy. 2. CV Optimization (Hyper-Personalized) — Upload your CV and receive a hyper-personalized positioning pipeline that combines your actual experience with deep insights from our career and workforce RAG knowledge base. Market analysis calibrated to your industry and seniority, career opportunity identification grounded in role/skill evolution data, and targeted edits with trade-off analysis — not generic advice, but intelligence shaped by 50+ premium research sources and your unique career trajectory.

Figma To Code Mcp By Bao To

THE BEST AND ONLY FIGMA MCP SERVER YOU WILL NEED While other Figma MCP servers can provide basic node information, Figma MCP Server by Bao To offers superior capabilities for understanding and utilizing your design system: - Comprehensive Design Data Extraction (get_figma_data): Fetches detailed information about your Figma files or specific nodes, simplifying complex Figma structures into a more digestible format for AI. - Precise Image Downloads (download_figma_images): Allows targeted downloading of specific image assets (SVGs, PNGs) from your Figma files. - ⭐ Automated Design Token Generation (generate_design_tokens): - Extracts crucial design tokens (colors, typography, spacing, effects) directly from your Figma file. Outputs a structured JSON file, ready to be integrated into your development workflow or used by AI to ensure design consistency. - ⭐ Intelligent Design System Documentation (generate_design_system_doc): - Goes beyond simple node data by generating comprehensive, multi-file Markdown documentation for your entire design system as defined in Figma. - Creates an organized structure including an overview, detailed pages for global styles (colors, typography, effects, layout), and component/node information per Figma canvas. This tool was a key motivation for this fork. By generating this comprehensive design system documentation directly within your project repository, it provides AI agents with a deep, contextual understanding of your project's specific design language. This empowers them to understand not just individual elements but the relationships and rules of your design system, leading to more accurate, consistent, and contextually aware UI implementation and freeing you from manual design interpretation. These advanced features make this server particularly powerful for tasks requiring a deep understanding of the design system, such as generating themed components or ensuring adherence to brand guidelines during UI development. This is a fork of Framelink's MCP server.