hierarchical-models

About hierarchical-models

hierarchical-models is a specialized agent skill created by benchflow-ai that extends AI coding assistants with enhanced capabilities. Agent skills provide context, workflows, and specialized knowledge that help AI assistants perform specific tasks more effectively than general-purpose AI alone.

Patterns for hierarchical/multilevel Bayesian models including random effects, partial pooling, and centered vs non-centered parameterizations.

How to use hierarchical-models

Once installed, hierarchical-models becomes available in your AI coding environment automatically. Your AI assistant will use the skill's instructions and knowledge whenever relevant tasks arise in your workflow. You can install it at the project level (available only in a specific project) or globally (available across all your projects).

Use the install panel on this page to copy a one-line command for your preferred AI client. The skill files are downloaded and placed in the appropriate directory — no additional configuration is required.

Compatible AI clients

hierarchical-models works with multiple AI coding assistants including Cursor, Claude Code, Codex, Copilot, and other agents that support the skills format. Each client stores skills in a slightly different directory, but the installation command handles this automatically.

What are agent skills?

Agent skills are reusable instruction sets that give AI coding assistants new capabilities. Unlike MCP servers that provide tools and API connections, skills provide context, workflows, and domain-specific knowledge. Think of skills as specialized training for your AI assistant — they help it understand particular frameworks, coding patterns, or development workflows.

Browse more skills in the skills directory or check out the leaderboard to see the most popular skills.

About the author

benchflow-ai has published 7 skills on MCP.Directory. Browse their full catalog to discover complementary skills for your workflow.