agentic-search-optimizer
OfficialOptimize content and interactive surfaces for agent-driven workflows.
Software Engineering#computer-use#deep-research#agentic-search#browsing-agents#agent-discoverability#llm-traversal
AuthorCanhada-Labs
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of ensuring that content and interactive surfaces are optimized for agent-driven workflows, enhancing task completion rates and discoverability.
Core Features & Use Cases
- Content Optimization: Designed for agent traversal and task completion, not human interaction.
- Task Completion: Focuses on the task-completion rate across agent-driven flows, not just search ranking.
- Use Case: Ideal for auditing AI agents' ability to complete tasks on a site or for implementing WebMCP markup on forms and interactive elements.
Quick Start
Use the agentic-search-optimizer skill to analyze the task completion rate for the 'example.com' site.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: agentic-search-optimizer Download link: https://github.com/Canhada-Labs/ceo-orchestration/archive/main.zip#agentic-search-optimizer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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