Agentation: Visual Feedback Tool That Turns UI Annotations Into Agent Actions
Agentation launched on Product Hunt on March 27 as the #1 product of the day, offering a visual feedback tool specifically designed for AI coding agents. The tool bridges the gap between what humans see on screen and what agents need to act on in code.
The workflow is straightforward: click on any UI element, annotate it with feedback (select text, draw areas, freeze animations, multi-select), and Agentation generates structured output with grep-friendly CSS selectors that coding agents can immediately use to locate the exact element in your codebase. Paste the annotation into Claude Code, Codex, or any AI tool and the feedback becomes working code.
Key to the product is its MCP integration, enabling two-way sync between humans and agents. AI agents can acknowledge, question, or resolve feedback directly through the MCP protocol, creating a closed feedback loop rather than a one-way annotation dump.
Agentation also includes smart element identification that automatically generates selectors, multiple annotation modes for different feedback types, and export formats optimized for agent consumption.
For the agentic ecosystem, Agentation addresses a fundamental bottleneck: the handoff between human visual perception and agent code execution. As coding agents become the primary way software gets built, the tools humans use to communicate with those agents need to speak the same structured language. Details at https://www.agentation.com.
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The workflow is straightforward: click on any UI element, annotate it with feedback (select text, draw areas, freeze animations, multi-select), and Agentation generates structured output with grep-friendly CSS selectors that coding agents can immediately use to locate the exact element in your codebase. Paste the annotation into Claude Code, Codex, or any AI tool and the feedback becomes working code.
Key to the product is its MCP integration, enabling two-way sync between humans and agents. AI agents can acknowledge, question, or resolve feedback directly through the MCP protocol, creating a closed feedback loop rather than a one-way annotation dump.
Agentation also includes smart element identification that automatically generates selectors, multiple annotation modes for different feedback types, and export formats optimized for agent consumption.
For the agentic ecosystem, Agentation addresses a fundamental bottleneck: the handoff between human visual perception and agent code execution. As coding agents become the primary way software gets built, the tools humans use to communicate with those agents need to speak the same structured language. Details at https://www.agentation.com.
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