How Agents Choose Tools? Ranking, Routing and Fallbacks
Discover the tool selection strategy of AI agents. How to optimize tool calling using advanced routing, ranking and multi-model fallback architectures.
LLM Tool Schema Design: Inputs, Outputs & Error Handling
Design tool schemas for LLM tool calling with clear inputs, outputs, validation, error handling and governance patterns for production AI agents.
Tool Calling for AI Agents: End-to-End Execution Flow
Learn how tool calling works for LLM agents, from tool selection and schema validation to execution, governance and enterprise deployment.
Agent Skills vs Prompts: Reuse, Control, QA at Scale
Agent Skills vs Prompts: learn when to use prompts, when to use reusable agent skills and how to improve control, QA and governance at scale.
AI Skills vs MCP Tools: When to Use Each in Production
AI Skills vs MCP Tools: learn when to use skills, MCP tools or both in production, with decision criteria, governance patterns and examples.
Versioning Agent Skills: SemVer, Compatibility, Deprecation
Learn how AI agent skills need SemVer, compatibility rules, and deprecation policies to keep developer agents stable, safe, and upgradeable.
Agent Tools vs Agent Skills: Practical Differences
Agent Tools vs Agent Skills explained for enterprise AI teams: learn how tools execute actions, how skills guide workflows, and when to use each.
AI Agent Governance: How to Run Scripts Safely
Master AI agent skills, establish robust agent governance and discover how to run scripts from agent skills safely in your enterprise workflows.
AI Agent Governance: Skill Permissions & Allowlist Tools
Master AI agent governance with strict skill permissions. Secure workflows using allowlist tools for agent skills.
Progressive Disclosure for AI Skills: Load When Needed
Master progressive disclosure for AI skills to optimize agent context windows and improve output quality by loading data only when needed.
