Claude Skills by mitkox

github.com/mitkox

24 skillsA× 20B× 43 installs82 views

AI Terminology SkillAThis skill ensures consistent, accurate usage of AI/ML terminology throughout the FTE+AI documentation, making content accessible to R&D audiences with varying AI expertise.documentationtypescriptpythonVotes: 0GitHub stars: 82
API Integration SkillAComprehensive expertise in integrating AI APIs and SDKs into enterprise development workflows, covering authentication, error handling, performance optimization, and multi-provider strategies.developmentpythongoVotes: 0GitHub stars: 82
Change Management SkillAExpertise in managing the human and organizational aspects of AI adoption, including stakeholder engagement, training, resistance management, and cultural transformation.businessrustgoVotes: 0GitHub stars: 82
Code Examples SkillAThis skill provides expertise in creating clear, accurate, and educational code examples for AI implementation guides in the FTE+AI project.documentationjavascripttypescriptVotes: 0GitHub stars: 82
Data Sovereignty SkillAExpertise in maintaining complete control over enterprise data in AI systems, ensuring data residency compliance, implementing privacy protections, and achieving regulatory compliance across jurisdictions.businesspythonrustVotes: 0GitHub stars: 82
Data Visualization SkillAExpertise in creating clear, impactful visualizations for metrics, comparisons, and trends in the FTE+AI documentation.documentationpythongoVotes: 0GitHub stars: 82
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Document Structure SkillBThis skill provides expertise in organizing complex technical documentation with clear hierarchies, logical flow, and intuitive navigation for R&D audiences. It ensures documents are scannable, navigable, and appropriately structured for their purpose and audience.documentationgoapiVotes: 0GitHub stars: 82
Financial Modeling SkillAExpertise in creating accurate, transparent financial models for AI adoption ROI calculations, vendor cost comparisons, and budget planning for R&D leaders.businessgoawsVotes: 0GitHub stars: 82
Hardware Sizing SkillAExpertise in calculating and specifying hardware requirements for local AI deployments, including GPU selection, server configuration, storage, and network planning based on workload characteristics and team size.devopsgonodeVotes: 0GitHub stars: 82
Legal Compliance SkillAExpertise in legal considerations for AI vendor replacement initiatives, covering contract law, intellectual property, data processing agreements, licensing compliance, and vendor exit procedures. This skill provides frameworks and templates but does not constitute legal advice.businessgoawsVotes: 0GitHub stars: 82
Local AI Deployment SkillBExpertise in deploying and configuring self-hosted LLM platforms for enterprise environments, ensuring data sovereignty, performance optimization, and production-grade reliability without external dependencies.devopsgobashVotes: 0GitHub stars: 82
Metrics & Analytics SkillAExpertise in designing, implementing, and analyzing metrics frameworks for AI-augmented teams, focusing on productivity measurement, ROI validation, and continuous improvement through data-driven insights.businessgoazureVotes: 0GitHub stars: 82
Milestone Tracking SkillAExpertise in tracking program milestones, deliverables, and dependencies throughout the 30-60-90 day vendor replacement program, ensuring visibility, accountability, and timely completion.businessgoapiVotes: 0GitHub stars: 82
MLOps Operations SkillAExpertise in operating and maintaining production AI/ML systems, including deployment pipelines, monitoring, incident response, capacity management, and continuous improvement for local LLM infrastructure.devopspythongoVotes: 0GitHub stars: 82
Open Source Licensing SkillAExpertise in navigating open-source licenses for AI models and tools, ensuring commercial compliance, managing license obligations, and mitigating intellectual property risks in enterprise AI deployments.devopspythongoVotes: 0GitHub stars: 82
Production Readiness SkillAExpertise in preparing AI-augmented teams and solutions for enterprise production deployment, including scalability, reliability, monitoring, and operational excellence requirements.devopsgotestingVotes: 0GitHub stars: 82
Program Planning SkillAExpertise in creating and executing vendor replacement programs using the proven 30-60-90 day framework, including milestone planning, resource allocation, dependency management, and phase gate governance.businessgogitVotes: 0GitHub stars: 82
Risk Assessment SkillBComprehensive expertise in identifying, analyzing, and mitigating risks associated with AI adoption for vendor replacement, covering security, compliance, business, and operational dimensions.businessrustgoVotes: 0GitHub stars: 82
Stakeholder Management SkillAExpertise in identifying, analyzing, engaging, and managing stakeholders throughout the vendor replacement program to ensure alignment, support, and successful outcomes.businessrustgoVotes: 0GitHub stars: 82
Technical Writing SkillAThis skill ensures clear, concise, and effective technical communication for R&D audiences with varying levels of AI expertise. It establishes standards for writing quality, style consistency, and audience-appropriate content that enables successful AI adoption.documentationpythongoVotes: 0GitHub stars: 82
Tool Evaluation SkillBStructured methodology for objectively evaluating, comparing, and selecting AI tools for vendor replacement initiatives, ensuring data-driven decisions.businessjavascriptpythonVotes: 0GitHub stars: 82
Vendor Negotiation SkillAExpertise in negotiating favorable terms with AI vendors, optimizing contracts, managing commercial relationships, and ensuring value alignment throughout the vendor lifecycle.businessgoazureVotes: 0GitHub stars: 82
Vendor Transition SkillASpecialized expertise in managing the complex process of transitioning from outsourcing vendors to AI-augmented internal teams, including contract management, knowledge transfer, and relationship navigation.businessgoexpressVotes: 0GitHub stars: 82
security-audit-rlmARun and troubleshoot privacy-preserving, local DSPy RLM security audits for large legacy .NET codebases. Use when asked to scan repositories for vulnerabilities, tune RLM/tool limits, fix truncation/stall issues, or produce actionable markdown/json audit outputs without loading entire codebases into model context.researchpythongitVotes: 0GitHub stars: 78