# Memorysaver Looplia Skills Browser Research > Browser Research - Skill: `tomevault-io/memorysaver-looplia-skills-browser-research` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/memorysaver-looplia-skills-browser-research` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/memorysaver-looplia-skills-browser-research/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/memorysaver-looplia-skills-browser-research --- # Browser Research ## Prerequisites This skill requires the `agent-browser` CLI tool from [vercel-labs/agent-browser](https://github.com/vercel-labs/agent-browser). ### Installation ```bash # Install the CLI globally npm install -g agent-browser # Install Chromium browser (required) agent-browser install ``` ### Verify Installation ```bash agent-browser --version agent-browser install --check ``` If you see version output and a successful browser check, you're ready to use this skill. Execute deep web research missions using agent-browser for interactive page navigation and data extraction. ## When to Use - **Multi-page research**: Navigating search results, following links, exploring sites - **Dynamic content**: JavaScript-rendered pages, SPAs, interactive dashboards - **Form interaction**: Filling search fields, applying filters, submitting queries - **Data extraction**: Tables, lists, product information, structured data - **Authenticated content**: Sites requiring login or session state For simple static pages, consider `WebFetch` first. Escalate to agent-browser when content is incomplete or interaction is required. ## Core Research Loop ``` ┌─────────────────────────────────────────────────────┐ │ 1. OPEN agent-browser open │ │ 2. SNAPSHOT agent-browser snapshot -i │ │ 3. EXTRACT agent-browser get text @ref │ │ 4. NAVIGATE agent-browser click @ref / fill / etc │ │ 5. REPEAT Loop steps 2-4 until mission complete │ └─────────────────────────────────────────────────────┘ ``` ### The Snapshot-Act Pattern Always snapshot before interacting. Refs (`@e1`, `@e2`) are stable identifiers for elements: ```bash agent-browser open "https://example.com/search" agent-browser snapshot -i # See what's available agent-browser fill @e3 "search query" # Fill the search box agent-browser click @e5 # Click search button agent-browser wait --load networkidle # Wait for results agent-browser snapshot -i # See new state ``` ## Research Planning Before starting, define: | Aspect | Question | Example | |--------|----------|---------| | **Mission** | What information do you need? | "Find pricing for top 3 CRM tools" | | **Sources** | Which sites to visit? | Specific URLs or search-discovered | | **Extraction** | What data points to capture? | Price, features, limits | | **Depth** | How many pages/levels? | First 10 results, 2 levels deep | ### Source Discovery Start broad, then narrow: ```bash # Option 1: Direct navigation (when you know the site) agent-browser open "https://known-site.com/pricing" # Option 2: Search engine discovery agent-browser open "https://www.google.com" agent-browser snapshot -i agent-browser fill @e1 "CRM pricing comparison 2025" agent-browser press Enter agent-browser wait --load networkidle agent-browser snapshot -i # Extract relevant URLs from results ``` ## Scenario Recipes Use recipes when you need a repeatable pattern. Each recipe should include: 1. **Intent** - The question being answered and the expected output shape 2. **Minimal Steps** - 3-6 steps with snapshots, verification, and stop conditions 3. **Output** - JSON fields with sources, access dates, and missing-data notes ### Extraction - [Data Extraction Patterns](references/data-extraction.md) - Feed top-N, paginated catalog, filtered results ### Comparison - [Multi-Source Research](references/multi-source.md) - Consensus checks, price/spec comparisons, recency validation ### Exploration - [Site Exploration](references/site-exploration.md) - Docs crawl, category discovery, auth-gated inventory ## Data Extraction Strategies ### Extract Text Content ```bash # Single element agent-browser get text @e15 # Multiple elements - snapshot shows structure agent-browser snapshot -s ".results" # Scope to results section agent-browser get text @e20 # First result agent-browser get text @e25 # Second result ``` ### Handle Pagination ```bash # Pattern: Extract current page, navigate to next, repeat agent-browser snapshot -i # ... extract data from current page ... agent-browser click @e99 # "Next" button agent-browser wait --load networkidle agent-browser snapshot -i # New page content ``` ### Handle Lazy Loading ```bash agent-browser scroll down 1000 agent-browser wait 1000 # Allow content to load agent-browser snapshot -i # See newly loaded content ``` ## Output Format Structure your research results for clarity: ```json { "mission": "Original research question", "sources": [ { "url": "https://example.com/page", "title": "Page Title", "accessed": "2025-01-19", "data": { "key_finding_1": "value", "key_finding_2": "value" } } ], "summary": "Key findings in 2-3 sentences", "limitations": "Any access issues or incomplete data" } ``` Always include: - **Source URLs** for attribution - **Access timestamps** for currency - **Limitations** for transparency ## Sessions for Parallel Research Use named sessions to research multiple sources simultaneously: ```bash # Research source A agent-browser --session src-a open "https://site-a.com" agent-browser --session src-a snapshot -i # Research source B (parallel) agent-browser --session src-b open "https://site-b.com" agent-browser --session src-b snapshot -i # Continue working in each session agent-browser --session src-a click @e5 agent-browser --session src-b fill @e3 "query" ``` ## Quick Reference For complete command documentation, see: [agent-browser CLI](https://github.com/vercel-labs/agent-browser) | Task | Command | |------|---------| | Navigate | `open`, `back`, `forward`, `reload`, `close` | | Analyze | `snapshot -i`, `get text/html/value/url/title` | | Interact | `click`, `fill`, `press`, `select`, `find` | | Wait | `wait --load`, `wait `, `wait ` | | State | `is visible`, `is enabled`, `state save/load` | | Capture | `screenshot`, `pdf`, `--json` | ## See Also - [Data Extraction Patterns](references/data-extraction.md) - Tables, lists, structured data - [Multi-Source Research](references/multi-source.md) - Comparing across sites - [Site Exploration](references/site-exploration.md) - Deep-diving single domains ## Handling Failures Research automation can fail. Handle common issues: ```bash # Check if element exists before interacting agent-browser is visible @e50 # If false, the page structure may have changed - re-snapshot # Timeout waiting for content agent-browser wait --load networkidle # If this times out, content may require scrolling or interaction # Element not found - try semantic locators agent-browser find text "Submit" click # More resilient than refs when DOM structure changes # Network errors - check page loaded agent-browser get url # Verify you're on the expected page before extracting ``` When failures occur: - **Re-snapshot** - DOM may have changed - **Try `find` locators** - More stable than refs for dynamic content - **Check URL** - Redirects or errors may have changed the page - **Report limitations** - Note access issues in output, don't silently skip ## Best Practices 1. **Snapshot frequently** - DOM changes after interactions 2. **Use `-i` flag** - Interactive elements only, cleaner output 3. **Wait after navigation** - `--load networkidle` ensures content is ready 4. **Scope when needed** - `-s ".container"` focuses on relevant sections 5. **Track sources** - Use `get url` and `get title` for attribution 6. **Handle failures** - Report access issues, don't silently skip 7. **Use `find` for dynamic content** - When refs change, semantic locators are more stable 8. **Close when done** - `agent-browser close` releases resources --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/memorysaver) — claim your Tome and manage your conversions.