dx-data-navigatorQuery Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team perfo...
Install via ClawdBot CLI:
clawdbot install Xiao1804/dx-data-navigatorGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 20, 2026
Engineering leaders use this skill to monitor DORA metrics like deployment frequency and lead time for changes across teams. They can compare team performance against industry benchmarks, track sprint velocity, and identify bottlenecks in code review cycles to drive productivity improvements.
Product managers and DX teams analyze survey data on developer sentiment, tool satisfaction (CSAT), and workflow metrics like CI wait time. This helps prioritize investments in tools and processes to reduce friction, improve engagement, and accelerate AI coding assistant adoption.
HR or analytics teams assess team effectiveness, impact, and quality scores from core4 metrics against organizational and industry percentiles. They use this to inform talent development, resource allocation, and identify high-performing teams for best practice sharing.
Data analysts track AI adoption rates by querying user adoption dates and correlating them with PR metrics like cycle times or code quality. This supports ROI analysis for AI tool investments and guides training programs to boost heavy adoption.
Site reliability engineers or quality assurance teams link deployment data with incident reports to analyze failure rates and mean time to recovery. They use workflow averages and sentiment data to assess how process changes affect developer confidence and operational stability.
Companies offer this skill as part of a SaaS platform where clients pay monthly or annual fees for access to real-time engineering analytics. Revenue is generated through tiered pricing based on data volume, number of teams, or advanced features like predictive insights.
Agencies or consultants use this skill to provide custom analytics solutions for clients, helping them set up queries, interpret data, and optimize workflows. Revenue comes from project-based fees, ongoing support contracts, and training workshops.
Large organizations license the skill internally, integrating it with their existing data warehouses or BI tools like Tableau. Revenue is generated through one-time license sales or annual enterprise agreements, often bundled with premium support and customization options.
💬 Integration Tip
Always query information_schema.columns first to verify table structures, and use GROUP BY with MAX() for team scores to avoid duplicates from snapshot history.
Scored Apr 19, 2026
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