Ai Agent Articles

What you'll learn:

• What AI agent skills are and how they differ from plugins.
• How progressive disclosure loads skills in 3 stages with minimal token cost.
• How to write a SKILL.md file with proper YAML frontmatter.
• How to build, test, debug, and share agent skills across platforms.

What you'll learn:

• AI agents plan, search, and verify across sources.
• Agentic search completes tasks autonomously.
• Optimize for discovery, clarity, and authority.
• Agentic site search uses multi-step retrieval.

What you'll learn:

• What agentic browsing is.
• How Lighthouse checks AI readiness.
• Five steps to optimize your site.
• Using WebMCP and llms.txt for AI agents.

What you'll learn:

• Discover why code intent over search volume determines AI agent keyword value
• Learn to mine GitHub trending for agent keyword triples across repositories
• Understand framework-anchored entity clusters versus generic topical buckets
• Master per-engine citation tracking across Claude Code, Codex, and ChatGPT

What you'll learn:

• 1. How 10 factors determine the best AI agent framework for your use case
• 2. A 12-framework comparison table with production-readiness ratings
• 3. Why MCP protocol support is the non-negotiable criteria in 2026
• 4. Which framework matches which task pattern: compliance, content, or coding

What you'll learn:

• What WebMCP is and how it works.
• Why WebMCP matters for AI agents.
• Declarative vs Imperative API.
• How WebMCP differs from traditional MCP.

What you'll learn:

• What the accessibility tree is.
• Why AI agents depend on it.
• How to check your tree in Chrome.
• Five common problems and fixes.