agentation-self-driving▌
benjitaylor/agentation · updated Apr 8, 2026
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Autonomous design critique mode that adds annotations to web pages via the Agentation toolbar in a visible browser.
- ›Requires the Agentation toolbar installed on the target page and the agent-browser skill available; launches in headed mode so users watch the agent scan, hover, and annotate in real time
- ›Uses coordinate-based mouse events to trigger annotation dialogs (standard element clicks do not work); includes helper patterns for scrolling, bounding box lookup, and dialog interaction
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:
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:
# 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:
# 1. Check toolbar exists on the page (data-feedback-toolbar is the root marker)
agent-browser eval "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('[data-feedback-toolbar][class*=expanded]') ? 'already expanded' : (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.
@refcompatibility: Onlyclick,fill,type,hover,focus,check,select,dragsupport@refsyntax. The commandsscrollintoview,get box, andevaldo NOT — they expect CSS selectors. UseevalwithquerySelectorfor scrolling and position lookup.
# 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:
agent-browser eval "document.querySelector('[data-feedback-toolbar][class*=expanded]') ? 'ok' : (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 line | CSS 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:
agent-browser eval "document.querySelector('h2').textContent"
The Loop
Work top-to-bottom through the page. For each annotation:
- Scroll to the target area via eval (
scrollIntoView) - Pick a specific element — heading, paragraph, button, section container
- Get its bounding box via eval (
getBoundingClientRect) - Execute the coordinate-click sequence (
mouse move→mouse down→mouse up) - Read the full snapshot output to find dialog refs at the bottom
- Write the critique (
fill @ref) and submit (click @ref) - Verify the annotation was added (see below)
- Move to the next area
Verifying annotations
After submitting each annotation, confirm the count increased:
agent-browser eval "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
| Area | What to look for |
|---|---|
| Hero / above the fold | Headline hierarchy, CTA placement, visual grouping |
| Navigation | Label styling, category grouping, visual weight |
| Demo / illustrations | Clarity, depth, animation readability |
| Content sections | Spacing rhythm, callout treatments, typography hierarchy |
| Key taglines | Whether resonant lines get enough visual emphasis |
| CTAs and footer | Conversion 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:
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/nullthen retry the--headed opencommand - Toolbar not found on page: Agentation isn't installed — run
/agentationto 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 closeto clean up before starting a new session
agent-browser Pitfalls
These will silently break the workflow if you're not aware of them:
| Pitfall | What happens | Fix |
|---|---|---|
scrollintoview @ref |
Crashes: "Unsupported token @ref while parsing css selector" | Use eval "document.querySelector('sel').scrollIntoView({block:'center'})" |
get box @ref |
Same crash — get box parses refs as CSS selectors |
Use eval "((r)=>r.x+','+r.y+','+r.width+','+r.height)(document.querySelector('sel').getBoundingClientRect())" |
eval with double-bang |
Bash expands double-bang as history substitution before the command runs | Use expr !== null or expr ? true : false instead |
eval with backslash-escaped quotes |
Escaped inner quotes break across shells | Drop the quotes: [class*=toggleContent] works for simple values without spaces |
snapshot -i | head -50 |
Annotation dialog refs (textbox "What should change?", Add, Cancel) appear at the BOTTOM of the snapshot |
Always read the full snapshot output — never truncate |
click @ref on overlay elements |
The click goes through to the real DOM, bypassing the Agentation overlay | Use 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 launches | Run 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_annotationsin 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.
How to use agentation-self-driving on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add agentation-self-driving
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches agentation-self-driving from GitHub repository benjitaylor/agentation and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate agentation-self-driving. Access the skill through slash commands (e.g., /agentation-self-driving) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★64 reviews- ★★★★★Sophia Zhang· Dec 28, 2024
I recommend agentation-self-driving for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Michael Khanna· Dec 28, 2024
Keeps context tight: agentation-self-driving is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Hiroshi Ramirez· Dec 24, 2024
I recommend agentation-self-driving for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Fatima Liu· Dec 20, 2024
agentation-self-driving is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Carlos Zhang· Dec 4, 2024
agentation-self-driving is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Sophia Diallo· Nov 23, 2024
agentation-self-driving reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Mateo Harris· Nov 19, 2024
Registry listing for agentation-self-driving matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Michael Perez· Nov 11, 2024
agentation-self-driving reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Mei Smith· Nov 7, 2024
Useful defaults in agentation-self-driving — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sophia Abebe· Oct 26, 2024
I recommend agentation-self-driving for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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