browser-screenshot▌
zc277584121/marketing-skills · updated Apr 8, 2026
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Take focused screenshots of specific regions on web pages — a Reddit post, a tweet, an article section, a chart, etc. — not just a full-page dump.
Skill: Browser Screenshot
Take focused screenshots of specific regions on web pages — a Reddit post, a tweet, an article section, a chart, etc. — not just a full-page dump.
Prerequisite: agent-browser must be installed and Chrome must have remote debugging enabled. See
references/agent-browser-setup.mdif unsure.
Overview
This skill handles the full pipeline:
- Research the best page to screenshot (web search, fetch)
- Navigate to the right page in the browser
- Locate the target element/region on the page
- Capture a focused, cropped screenshot of just that region
Hard Rule: No Full-Screen Screenshots
NEVER output an uncropped full-viewport or full-page screenshot as a final result. Full screenshots contain too much noise (nav bars, sidebars, ads, unrelated content) and are unsuitable as article illustrations. Every screenshot MUST be cropped to a focused region.
Step 0: Research — Find and Validate Sources Before Opening the Browser
The browser is for capturing, not for browsing. Before opening anything in Chrome, use text-based tools (WebSearch, WebFetch) to find candidate pages, read their content, and decide which ones are actually worth screenshotting.
Research-First Workflow
- WebSearch to find candidate pages for the topic
- WebFetch each candidate to read its text content — check if it has the information/visual you need
- Evaluate: Is this page worth a screenshot? Does it have a clear, focused region that would work as an illustration?
- Only then open the browser to capture the screenshot
This saves significant time — most candidate pages won't be worth screenshotting, and you can eliminate them without the overhead of browser navigation.
When to Use Browser-First Instead
Skip the WebSearch/WebFetch phase and go directly to Chrome browsing when:
- The target platform requires login — Reddit, LinkedIn, X/Twitter, and other social platforms often gate content behind login walls. If the user's Chrome session is already logged in, use the browser directly.
- The user specifies a platform with a clear search need — e.g., "find a Reddit post about X" or "screenshot a tweet about Y". Go straight to the platform's search in Chrome.
- WebFetch returns blocked/incomplete content — some sites aggressively block non-browser requests. If you get a 403, a CAPTCHA page, or stripped content, switch to Chrome.
In these cases, Chrome browsing replaces WebSearch — navigate to the platform's search page, browse results, and evaluate pages visually before deciding what to screenshot.
Page Selection Strategy
The right page depends on the context of the article and how recent/notable the subject is:
| Subject Type | Best Page to Find | How to Find It |
|---|---|---|
| New model/feature launch (< 6 months) | Official blog post announcing it | WebSearch "<model name>" site:<vendor-domain> blog |
| Established product (> 6 months) | Product landing page or docs overview | WebSearch "<model name>" official page |
| Open-source model | HuggingFace model card or GitHub repo | Direct URL: huggingface.co/<org>/<model> |
| API service | API documentation page | WebSearch "<service name>" API docs |
Note: This table lists common subject types but is not exhaustive. Apply the same research-first strategy to any subject type — find the most authoritative and visually clean source page for the topic at hand.
What Makes a Good Screenshot Source
Core principle: Less is more. Focus on content, not chrome.
A good screenshot source contains a focused, self-contained piece of information — a paragraph of text, a key quote, a data table, a diagram. It should NOT be a busy page full of buttons, navigation, sidebars, and interactive elements.
- Prefer: A section of a blog post with a clear heading and 1-2 paragraphs of text. A single chart or diagram. A model card header with name and description. A quote or key finding.
- Avoid: Full landing pages with CTAs and navigation. Dashboard views with multiple panels. Pages dominated by UI controls (buttons, dropdowns, forms) rather than readable content.
- Official blog posts are ideal: they have hero images, prominent titles, and concise descriptions designed for sharing
- Product landing pages can work but only if you crop to the hero section — ignore the rest
- HuggingFace model cards are reliable for open-source models: consistent layout, model name + description always at top
- API docs are acceptable fallback: show the product name and key specs
Rule of thumb: If the region you plan to capture contains more interactive UI elements (buttons, links, nav items) than readable text content, it's a bad crop. Find a more content-rich region, or pick a different page entirely.
Pre-Flight URL Validation
Before opening in the browser, validate URLs with WebFetch (lightweight HEAD/GET) to avoid wasting time on 404s or redirects:
WebFetch: <candidate-url>
→ Check status code, title, and content snippet
→ If 404 or redirect to unrelated page, try next candidate
Region Selection Strategy
Think about what the article reader needs to see in this screenshot:
| Article Context | What to Capture | Target Region |
|---|---|---|
| Introducing a model in a lineup | Model name + key tagline/description | Blog hero section or HF model card header |
| Comparing capabilities | Feature highlights or spec table | Blog section showing specs/features |
| Discussing a specific feature | The feature description | Relevant section heading + 1-2 paragraphs |
| Showing a product/service | Brand identity + value prop | Landing page hero (title + subtitle + visual) |
The screenshot should make the reader think "ah, that's what this model/product is" — not "what am I looking at?"
Step 1: Navigate to the Target Page
Always Start by Listing Tabs
agent-browser --auto-connect tab list
Check if the page is already open. Reuse existing tabs — they have login sessions and correct state.
Navigation by Input Type
| User Provides | Strategy |
|---|---|
| Direct URL | agent-browser --auto-connect open <url> |
| Search query | open https://www.google.com/search?q=<encoded-query> → find and click the best result |
| Platform + topic | Construct platform search URL (see below) → locate target content |
| Vague description | Google search → evaluate results → navigate to best match |
Platform-Specific Search URLs
| Platform | Search URL Pattern |
|---|---|
https://www.reddit.com/search/?q=<query> |
|
| X / Twitter | https://x.com/search?q=<query> |
https://www.linkedin.com/search/results/content/?keywords=<query> |
|
| Hacker News | https://hn.algolia.com/?q=<query> |
| GitHub | https://github.com/search?q=<query> |
| YouTube | https://www.youtube.com/results?search_query=<query> |
Wait for Page Load
After navigation, wait for content to settle:
agent-browser --auto-connect wait --load networkidle
Note: Some sites (Reddit, X, LinkedIn) never reach
networkidle. Ifopenalready shows the page title in its output, skip the wait. Usewait 2000as a safe alternative.
Step 2: Locate the Target Region
This is the critical step. The goal is to find a CSS selector that precisely wraps the content to capture.
Primary Method: DOM Selector Discovery
-
Take an annotated screenshot to understand the page layout:
agent-browser --auto-connect screenshot --annotate -
Take a snapshot to see the page's accessibility tree:
agent-browser --auto-connect snapshot -i -
Identify the target container element. Look for:
- Semantic HTML containers:
<article>,<main>,<section> - Platform-specific components (see Platform Selectors)
- Data attributes:
[data-testid="..."],[data-id="..."]
- Semantic HTML containers:
-
Verify with
get boxto confirm the element has a reasonable bounding box:agent-browser --auto-connect get box "<selector>"This returns
{ x, y, width, height }. Sanity-check:- Width should be > 100px and < viewport width
- Height should be > 50px
- If the box is the entire page, the selector is too broad — refine it
-
If the selector is hard to find, use
evalto explore the DOM:agent-browser --auto-connect eval "document.querySelector('article')?.getBoundingClientRect()"
Platform Selectors
Common container selectors for popular platforms:
| Platform | Target | Typical Selector |
|---|---|---|
| A post | shreddit-post, [data-testid="post-container"] |
|
| X / Twitter | A tweet | article[data-testid="tweet"] |
| A feed post | .feed-shared-update-v2 |
|
| Hacker News | A story + comments | #hnmain .fatitem |
| GitHub | A repo card | [data-hpc], .repository-content |
| YouTube | Video player area | #player-container-outer |
| Generic article | Main content | article, main, [role="main"], .post-content, .article-body |
These selectors may change over time. Always verify with
get boxbefore using.
Multiple Matching Elements
If the selector matches multiple elements (e.g., multiple tweets on a timeline), narrow it down:
# Count matches
agent-browser --auto-connect get count "article[data-testid='tweet']"
# Use nth-child or :first-of-type, or a more specific selector
# Or use eval to find the right one by text content:
agent-browser --auto-connect eval --stdin <<'EOF'
const posts = document.querySelectorAll('article[data-testid="tweet"]');
for (let i = 0; i < posts.length; i++) {
const text = posts[i].textContent.substring(0, 80);
console.log(i, text);
}
EOF
Then target a specific one using :nth-of-type(N) or a unique parent selector.
Step 3: Capture the Focused Screenshot
Method A: Scroll + Viewport Screenshot (Preferred for Viewport-Sized Targets)
Best when the target element fits within the viewport.
# Scroll the target into view
agent-browser --auto-connect scrollintoview "<selector>"
agent-browser --auto-connect wait 500
# Take viewport screenshot
agent-browser --auto-connect screenshot /tmp/browser-screenshot-raw.png
Then crop using the bounding box (see Cropping).
Method B: Full-Page Screenshot + Crop (For Any Size Target)
Best when the target might be larger than the viewport or when precise cropping is needed.
# Take full-page screenshot
agent-browser --auto-connect screenshot --full /tmp/browser-screenshot-full.png
# Get the target element's bounding box
agent-browser --auto-connect get box "<selector>"
# Output: { x: 200, y: 450, width: 680, height: 520 }
Then crop (see Cropping).
Cropping
Use ImageMagick (magick on IMv7, convert is deprecated) to crop the screenshot to the target region. Add padding for visual breathing room.
Retina Display Handling
Critical: On macOS Retina displays, screenshots are captured at 2x resolution. A 1728x940 viewport produces a 3456x1880 image. You MUST account for this:
-
Detect the scale factor: Compare viewport size vs actual image dimensions:
# Check actual image dimensions magick identify /tmp/screenshot.png # → 3456x1880 means 2x scale on a 1728x940 viewport -
Multiply
get boxcoordinates by the scale factor before cropping:# get box returns viewport coordinates: { x: 200, y: 450, width: 680, height: 520 } # For 2x Retina, actual image coordinates are: SCALE=2 X=$((200 * SCALE)) Y=$((450 * SCALE)) W=$((680 * SCALE)) H=$((520 * SCALE)) PADDING=$((16 * SCALE))
Crop Command
magick /tmp/browser-screenshot-full.png \
-crop $((W + PADDING*2))x$((H + PADDING*2))+$((X - PADDING))+$((Y - PADDING)) \
+repage \
<output-path>.png
Important:
get boxreturns floating-point values. Round them to integers before passing to ImageMagick.
Padding: Use 12–20px (viewport px). Increase to ~30px if the target has a distinct visual boundary (card, bordered box). Use 0 if the user wants a tight crop.
Output Path
- If the user specifies an output path, use that
- Otherwise, save to a descriptive name in the current directory, e.g.,
reddit-post-screenshot.png,tweet-screenshot.png
Step 4: Verify the Result
After cropping, read the output image to verify it captured the right content:
# Use the Read tool to visually inspect the cropped screenshot
If the crop is wrong (missed content, too much whitespace, wrong element), adjust the selector or bounding box and retry.
Fallback: Visual Highlight Confirmation
When DOM-based location is uncertain — the selector might be wrong, multiple candidates exist, or the target is ambiguous — use JS-injected highlighting to visually confirm before cropping.
How It Works
-
Inject a highlight border on the candidate element:
agent-browser --auto-connect eval --stdin <<'EOF' (function() { const el = document.querySelector('<selector>'); if (!el) { console.log('NOT_FOUND'); return; } el.style.outline = '4px solid red'; el.style.outlineOffset = '2px'; el.scrollIntoView({ block: 'center' }); })(); EOF -
Take a screenshot and visually inspect:
agent-browser --auto-connect screenshot /tmp/highlight-check.pngRead the screenshot to check if the red border surrounds the correct content.
-
If correct
How to use browser-screenshot 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 browser-screenshot
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches browser-screenshot from GitHub repository zc277584121/marketing-skills 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 browser-screenshot. Access the skill through slash commands (e.g., /browser-screenshot) 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
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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★★★★★51 reviews- ★★★★★Dhruvi Jain· Dec 28, 2024
browser-screenshot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Charlotte Park· Dec 28, 2024
I recommend browser-screenshot for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sophia Ramirez· Dec 24, 2024
Useful defaults in browser-screenshot — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Alexander Thomas· Dec 16, 2024
Keeps context tight: browser-screenshot is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aanya White· Dec 12, 2024
Registry listing for browser-screenshot matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aditi Taylor· Nov 27, 2024
browser-screenshot reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Oshnikdeep· Nov 19, 2024
Keeps context tight: browser-screenshot is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Nia Nasser· Nov 15, 2024
browser-screenshot has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Alexander Li· Nov 7, 2024
browser-screenshot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Emma Malhotra· Nov 3, 2024
Solid pick for teams standardizing on skills: browser-screenshot is focused, and the summary matches what you get after install.
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