Expert guidance on validating, optimizing, and ensuring quality of Mapbox styles through validation, accessibility checks, and optimization. Use when preparing styles for production, debugging...

Build scalable data pipelines, modern data warehouses, and

Build scalable data pipelines, modern data warehouses, and

Build scalable data pipelines, modern data warehouses, and

Build scalable data pipelines, modern data warehouses, and

Build scalable data pipelines, modern data warehouses, and

just a general classification program

|

Analyze code complexity, cyclomatic complexity, maintainability index, and code churn using metrics tools. Use when assessing code quality, identifying refactoring candidates, or monitoring technical debt.

Business Model and Architecture Design methodology for aligning technical architecture with business model sustainability and scalability

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM...

Automated vulnerability detection using OWASP tools, CVE databases, and security scanners. Use when performing security audits, compliance checks, or continuous security monitoring.

Performs Codex-assisted project health diagnostics, identifies capability gaps, and produces prioritized improvement plans.

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or...

Use when discussing or working with DeepEval (the python AI evaluation framework)