Deterministic browser automation for AI agents with snapshot-based element references and multi-session support.
Works with
Interact with web pages using stable element refs (@e1, @e2, etc.) generated from snapshots, enabling reliable automation across DOM changes
Core commands cover navigation, form filling, clicking, waiting, screenshots, PDFs, and visual regression testing via baseline comparison
Supports parallel isolated sessions, network-aware waits (networkidle), and selector-based targe
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionagent-browserExecute the skills CLI command in your project's root directory to begin installation:
Fetches agent-browser from supercent-io/skills-template and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate agent-browser. Access via /agent-browser in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Always use the deterministic ref loop:
agent-browser open <url>agent-browser snapshot -i@e1, @e2, ...)agent-browser snapshot -i again after page/DOM changesagent-browser open https://example.com/form
agent-browser wait --load networkidle
agent-browser snapshot -i
agent-browser fill @e1 "[email protected]"
agent-browser click @e2
agent-browser snapshot -i
Use && chaining when intermediate output is not needed.
# Good chaining: open -> wait -> snapshot
agent-browser open https://example.com && agent-browser wait --load networkidle && agent-browser snapshot -i
# Separate calls when output is needed first
agent-browser snapshot -i
# parse refs
agent-browser click @e2
High-value commands:
open, closesnapshot -i, snapshot -i -C, snapshot -s "#selector"click, fill, type, select, check, pressdiff snapshot, diff screenshot --baseline <file>screenshot, screenshot --annotate, pdfwait --load networkidle, wait <selector|@ref|ms>Use explicit evidence after actions.
# Baseline -> action -> verify structure
agent-browser snapshot -i
agent-browser click @e3
agent-browser diff snapshot
# Visual regression
agent-browser screenshot baseline.png
agent-browser click @e5
agent-browser diff screenshot --baseline baseline.png
wait --load networkidle or selector/ref waits over fixed sleeps.eval --stdin (or base64) to avoid shell escaping breakage.--session <name>.Optional hardening examples:
# Wrap page content with boundaries to reduce prompt-injection risk
export AGENT_BROWSER_CONTENT_BOUNDARIES=1
# Limit output volume for long pages
export AGENT_BROWSER_MAX_OUTPUT=50000
# Restrict navigation and network to trusted domains
export AGENT_BROWSER_ALLOWED_DOMAINS="example.com,*.example.com"
# Restrict allowed action types
export AGENT_BROWSER_ACTION_POLICY=./policy.json
Example policy.json:
{"default":"deny","allow":["navigate","snapshot","click","fill","scroll","wait","get"],"deny":["eval","download","upload","network","state"]}
CLI-flag equivalent:
agent-browser --content-boundaries --max-output 50000 --allowed-domains "example.com,*.example.com" --action-policy ./policy.json open https://example.com
command not found: install and run agent-browser install.snapshot -i again and use fresh refs.--load networkidle or targeted wait selector.--session names and close each session.-i, -c, -d, -s) and extract only needed text.Deep-dive docs in this skill:
Related resources:
Ready templates:
./templates/form-automation.sh./templates/capture-workflow.shMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
supercent-io/skills-template
manaflow-ai/cmux
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
We added agent-browser from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: agent-browser is focused, and the summary matches what you get after install.
agent-browser has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend agent-browser for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: agent-browser is the kind of skill you can hand to a new teammate without a long onboarding doc.
agent-browser fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: agent-browser is focused, and the summary matches what you get after install.
I recommend agent-browser for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added agent-browser from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
agent-browser has been reliable in day-to-day use. Documentation quality is above average for community skills.
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