agentation_skill

This skill helps you annotate UI elements for AI agents by capturing CSS selectors and component trees to target code precisely.
  • Shell

24

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill supercent-io/skills-template --skill agentation

  • SKILL.md24.7 KB
  • SKILL.toon3.0 KB

Overview

This skill is a visual UI annotation bridge that lets humans click elements in any React app and deliver precise, machine-readable targets to AI agents. It captures CSS selectors, bounding boxes, and React component trees so agents can locate the exact code to change. Use it copy-paste style for one-off reviews or connect it to a local MCP server for a continuous watch-loop with agent automation.

How this skill works

A small React toolbar is dropped into your app; when a human clicks an element and leaves feedback the tool records elementPath (CSS selector), bounding box, and the React component tree. In Copy-Paste mode the toolbar exports markdown the human pastes into agent chat. In Agent Sync mode the toolbar talks to a local MCP server which exposes APIs and CLI tools so agents can poll, acknowledge, fix, and resolve annotations programmatically.

When to use it

  • When a human needs to point at a UI element without writing selectors
  • During iterative UI/UX review cycles between designers and coding agents
  • To build an agent watch-loop that auto-fixes user annotations
  • When you need precise targets (CSS selector, bounding box, React tree) to modify code reliably
  • To inject visual feedback into agent prompts via platform hooks or webhooks

Best practices

  • Run the toolbar only in development or testing environments to avoid user-facing overhead
  • Use MCP Agent Sync for iterative, automated fix loops; Copy-Paste works for ad-hoc feedback
  • Prefer elementPath (CSS selector) and React tree together to reduce false positives when searching code
  • Acknowledge annotations in the agent before making changes, then resolve with a short summary
  • Configure webhookUrl or onSubmit callbacks to integrate annotations into CI or issue trackers

Example use cases

  • Designer clicks a misaligned button, copies the annotation into agent chat; agent greps selector and suggests CSS tweaks
  • Developer enables Agent Sync; the agent blocks on agentation_watch_annotations and auto-applies small UI fixes as annotations arrive
  • QA team captures failing UI states and posts annotations to a webhook that files reproducible bug reports with selectors and screenshots
  • Autonomous critique: run agent-browser with agentation to let an agent review UI elements and post improvement suggestions
  • Integrate with Claude/Codex/Gemini/OpenCode MCP hooks so pending annotations auto-append to each agent message

FAQ

No. Copy-Paste mode works without a server for manual workflows. Use the MCP server for automated watch-loops and integrations.

How does an agent find the right code to change?

Each annotation includes an elementPath (CSS selector), bounding box, and React component tree. Agents can grep the selector or search the component tree to locate the exact source files.

Which agent platforms are supported?

It integrates with any MCP-compatible agent and provides prebuilt hooks for Claude Code, Codex CLI, Gemini CLI, and OpenCode; a universal npx add-mcp installer simplifies setup.

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