Muratcankoylan

This skill helps you design and run multi-dimensional evaluation for agent systems, enabling robust benchmarking, continuous improvement, and quality gates.

This skill helps you design and implement multi-agent systems with context isolation, coordination patterns, and scalable architectures.

This skill models agent beliefs, desires, and intentions from RDF context, enabling explainable BDI reasoning and coherent multi-agent coordination.

This skill helps you understand and design efficient context windows for AI agents, optimizing loading and budgeting across systems.

This skill helps manage and compress long agent conversations by optimizing tokens-per-task through anchored summaries and structured artifact tracking.

This skill enables building and validating author-style fine-tuning pipelines from ePub to LoRA-trainable models for book voices.

This skill helps you design and evaluate LLM-backed projects, selecting architecture, tasks, and cost estimates for efficient agent development.

This skill helps design and optimize agent tools, improving tool descriptions, consolidation, and interfaces for reliable multi-agent systems.

This skill enables automated LLM-based evaluation pipelines, compares model outputs, and mitigates biases to deliver consistent, objective quality assessments.

This skill helps ensure thorough validation, error handling, and transparent reasoning across multi-source research tasks.

This skill helps you design, optimize, and debug production agent systems through context engineering best practices and multi-agent architectures.

This skill analyzes your content, learns your voice, and iterates with deep research to produce publish-ready copy that sounds authentic.