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Agentation Self Driving

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benjitaylor
agentation-self-driving

Autonomous design critique mode using the Agentation annotation toolbar. Use when the user asks to "critique this page," "add design annotations," "review the UI," "self-driving mode," "auto-annotate," or wants an AI agent to autonomously add design feedback annotations to a web page via the browser. Requires the Agentation toolbar to be installed on the target page and agent-browser skill to be available.

Overview

Publisherbenjitaylor
Repositoryagentation
Skill nameagentation-self-driving
Stars
4.8K
Forks
390
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by benjitaylor on GitHub. Read the source before you install it.

Installation

Install the Agentation Self Driving AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/benjitaylor/agentation/tree/main/skills/agentation-self-driving
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/benjitaylor/agentation.git /tmp/agentation
mkdir -p .claude/skills
cp -r /tmp/agentation/skills/agentation-self-driving .claude/skills/agentation-self-driving
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agentation Self Driving in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agentation Self Driving on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agentation Self Driving is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agentation Self-Driving Mode

Autonomously critique a web page by adding design annotations via the Agentation toolbar — in a visible headed browser so the user can watch the agent work in real time, like watching a self-driving car navigate.

Launch — Always Headed

The browser MUST be visible. Never run headless. The user watches you scan, hover, click, and annotate.

Preflight: Verify agent-browser is available before anything else:

bash
command -v agent-browser >/dev/null || { echo "ERROR: agent-browser not found. Install the agent-browser skill first."; exit 1; }

Launch: Try opening directly first. Only close an existing session if the open command fails with a stale session error — this avoids killing a browser someone else is using:

bash
# Try to open. If it fails (stale session), close first then retry.
agent-browser --headed open <url> 2>&1 || { agent-browser close 2>/dev/null; agent-browser --headed open <url>; }

Then verify the Agentation toolbar is present and expand it:

bash
# 1. Check toolbar exists on the page. Agentation 3.1+ renders inside a shadow root on <agentation-toolbar>,
#    so query through it (the fallback to document keeps older versions working)
agent-browser eval "(document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelector('[data-feedback-toolbar]') ? 'toolbar found' : 'NOT FOUND'"
# If "NOT FOUND": Agentation is not installed on this page — stop and tell the user

# 2. Expand ONLY if collapsed (clicking when already expanded collapses it)
agent-browser eval "(document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelector('[data-feedback-toolbar][class*=expanded]') ? 'already expanded' : ((document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelector('[class*=toggleContent]')?.click(), 'expanding')"

# 3. Verify: take a snapshot and look for toolbar controls
agent-browser snapshot -i
# If expanded: you'll see "Block page interactions" checkbox, color buttons (Purple, Blue, etc.)
# If collapsed: you'll only see the small toggle button — retry step 2

"Block page interactions" must be checked (default: on).

eval quoting rule: Always use [class*=toggleContent] (no quotes around the attribute value) in eval strings. Do not use double-bang in eval because bash treats it as history expansion. Do not use backslash-escaped inner quotes either, as they break unpredictably across shells.

Critical: How to Create Annotations

Standard element clicks (click @ref) do NOT trigger annotation dialogs. The Agentation overlay intercepts pointer events at the coordinate level. Use coordinate-based mouse events — this also makes the interaction visible in the browser as the cursor moves across the page.

@ref compatibility: Only click, fill, type, hover, focus, check, select, drag support @ref syntax. The commands scrollintoview, get box, and eval do NOT — they expect CSS selectors. Use eval with querySelector for scrolling and position lookup.

bash
# 1. Take interactive snapshot — identify target element and build a CSS selector
agent-browser snapshot -i
# Example: snapshot shows  heading "Point at bugs." [ref=e10]
# Derive a CSS selector: 'h1', or more specific: 'h1:first-of-type'

# 2. Scroll the element into view via eval (NOT scrollintoview @ref — that breaks)
agent-browser eval "document.querySelector('h1').scrollIntoView({block:'center'})"

# 3. Get its bounding box via eval (NOT get box @ref — that also breaks)
agent-browser eval "((r) => r.x+','+r.y+','+r.width+','+r.height)(document.querySelector('h1').getBoundingClientRect())"
# Returns: "383,245,200,40"  (parse these as x,y,width,height)

# 4. Move cursor to element center, then click
#    centerX = x + width/2,  centerY = y + height/2
agent-browser mouse move <centerX> <centerY>
agent-browser mouse down left
agent-browser mouse up left

# 5. Get the annotation dialog refs — read the FULL snapshot output
#    Dialog refs appear at the BOTTOM of the list, don't truncate with head/tail
agent-browser snapshot -i
# Look for: textbox "What should change?" and "Cancel" / "Add" buttons

# 6. Type critique — fill and click DO support @ref
agent-browser fill @<textboxRef> "Your critique here"

# 7. Submit (Add button enables after text is filled)
agent-browser click @<addRef>

If no dialog appears after clicking, the toolbar may have collapsed. Re-expand (only if collapsed) and retry:

bash
agent-browser eval "(document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelector('[data-feedback-toolbar][class*=expanded]') ? 'ok' : ((document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelector('[class*=toggleContent]')?.click(), 'expanded')"

Building CSS selectors from snapshots

The snapshot shows element roles, names, and refs. Map them to CSS selectors:

Snapshot lineCSS selector
heading "Point at bugs." [ref=e10]h1 or h1:first-of-type
button "npm install agentation Copy" [ref=e15]button:has(code) or by text content via eval
link "Star on GitHub" [ref=e28]a[href*=github]
paragraph (long text...) [ref=e20]Target by section: section:nth-of-type(2) p

When in doubt, use a broader selector and verify with eval:

bash
agent-browser eval "document.querySelector('h2').textContent"

The Loop

Work top-to-bottom through the page. For each annotation:

  1. Scroll to the target area via eval (scrollIntoView)
  2. Pick a specific element — heading, paragraph, button, section container
  3. Get its bounding box via eval (getBoundingClientRect)
  4. Execute the coordinate-click sequence (mouse move → mouse down → mouse up)
  5. Read the full snapshot output to find dialog refs at the bottom
  6. Write the critique (fill @ref) and submit (click @ref)
  7. Verify the annotation was added (see below)
  8. Move to the next area

Verifying annotations

After submitting each annotation, confirm the count increased:

bash
agent-browser eval "(document.querySelector('agentation-toolbar')?.shadowRoot || document).querySelectorAll('[data-annotation-marker]').length"
# Should return the expected count (1 after first, 2 after second, etc.)

If the count didn't increase, the submission failed silently — re-snapshot and check if the dialog is still open.

Aim for 5-8 annotations per page unless told otherwise.

What to Critique

AreaWhat to look for
Hero / above the foldHeadline hierarchy, CTA placement, visual grouping
NavigationLabel styling, category grouping, visual weight
Demo / illustrationsClarity, depth, animation readability
Content sectionsSpacing rhythm, callout treatments, typography hierarchy
Key taglinesWhether resonant lines get enough visual emphasis
CTAs and footerConversion weight, visual separation, final actions

Critique Style

2-3 sentences max per annotation:

  • Specific and actionable: "Stack the install command below the subheading at 16px" not "fix the layout"
  • 1-2 concrete alternatives: Reference CSS values, layout patterns, or design systems
  • Name the principle: Visual hierarchy, Gestalt grouping, whitespace, emphasis, conversion design
  • Reference comparable products: "Like how Stripe/Linear/Vercel handles this"

Bad: "This section needs work" Good: "This bullet list reads like docs, not a showcase. Use a 3-column card grid with icons — similar to Stripe's guidelines pattern. Creates visual rhythm and scannability."

Install

The skill must be symlinked into ~/.claude/skills/ for Claude Code to discover it:

bash
ln -s "$(pwd)/skills/agentation-self-driving" ~/.claude/skills/agentation-self-driving

Restart Claude Code after installing. Verify with /agentation-self-driving — if it loads the skill instructions, the symlink is working.

Troubleshooting

  • "Browser not launched. Call launch first.": Stale session from a previous run — run agent-browser close 2>/dev/null then retry the --headed open command
  • Toolbar not found on page: Agentation isn't installed — run /agentation to set it up first
  • No dialog after clicking: Toolbar collapsed — re-expand with the state-aware eval (check [class*=expanded] first), retry
  • Wrong element targeted: Click Cancel, scroll to intended element, retry with correct coordinates
  • Add button stays disabled: Text wasn't filled — re-snapshot and fill the textbox
  • Page navigated: "Block page interactions" is off — enable via toolbar settings
  • Annotation count didn't increase: Submission failed — dialog may still be open, re-snapshot and check
  • Interrupted mid-run (Ctrl+C): The browser stays open with whatever state it was in. Run agent-browser close to clean up before starting a new session

agent-browser Pitfalls

These will silently break the workflow if you're not aware of them:

PitfallWhat happensFix
scrollintoview @refCrashes: "Unsupported token @ref while parsing css selector"Use eval "document.querySelector('sel').scrollIntoView({block:'center'})"
get box @refSame crash — get box parses refs as CSS selectorsUse eval "((r)=>r.x+','+r.y+','+r.width+','+r.height)(document.querySelector('sel').getBoundingClientRect())"
eval with double-bangBash expands double-bang as history substitution before the command runsUse expr !== null or expr ? true : false instead
eval with backslash-escaped quotesEscaped inner quotes break across shellsDrop the quotes: [class*=toggleContent] works for simple values without spaces
snapshot -i | head -50Annotation dialog refs (textbox "What should change?", Add, Cancel) appear at the BOTTOM of the snapshotAlways read the full snapshot output — never truncate
click @ref on overlay elementsThe click goes through to the real DOM, bypassing the Agentation overlayUse mouse move → mouse down left → mouse up left for coordinate-based clicks that the overlay intercepts
--headed open fails with "Browser not launched"Stale sessions from previous runs block new launchesRun agent-browser close 2>/dev/null then retry the open command

Rule of thumb: @ref works for interaction commands (click, fill, type, hover). For everything else (eval, get, scrollintoview), use CSS selectors via querySelector in an eval.

Two-Session Workflow (Full Self-Driving)

With MCP connected (toolbar shows "MCP Connected"), annotations auto-send to any listening agent. This enables:

  • Session 1 (this skill): Watches the page, adds critique annotations in the visible browser
  • Session 2: Runs agentation_watch_annotations in a loop, receives annotations, edits code to address each one

The user watches Session 1 drive through the page in the browser while Session 2 fixes issues in the codebase — fully autonomous design review and implementation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agentation Self Driving AI skill do?

Autonomous design critique mode using the Agentation annotation toolbar. Use when the user asks to "critique this page," "add design annotations," "review the UI," "self-driving mode," "auto-annotate," or wants an AI agent to autonomously add design feedback annotations to a web page via the browser. Requires the Agentation toolbar to be installed on the target page and agent-browser skill to be available.

Why use Agentation Self Driving on TypingMind?

Because you install it once and use it with any model. Agentation Self Driving is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agentation Self Driving in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/benjitaylor/agentation/tree/main/skills/agentation-self-driving. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agentation Self Driving?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agentation Self Driving?

As many as you like. As long as a model supports skills, you can use Agentation Self Driving with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agentation Self Driving AI skill free?

It is published on GitHub by benjitaylor. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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