Xpersona
A

Agent Browser

CLAWHUB · Unverified

Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection Skill: Agent Browser Owner: matrixy Summary: Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection Tags: latest:0.1.0 Version history: v0.1.0 | 2026-01-21T22:00:54.381Z | auto - Initial release of agent-browser-clawdbot skill. - Enables fast, headless browser automation via CLI, optimized for AI agent workflows. - Provides accessibility tree snapshot

62
Rank
84
Safety
160k
Downloads

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 159.5K downloads reported by the source. Last updated 11/11/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Install and run

Setup complexity: low.

clawhub skill install s17e24j3hd5g35an84aqwke9px88507e:agent-browser-clawdbot
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-matrixy-agent-browser-clawdbot-clawdbot-2/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

8,835 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: agent-browser
description: Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
metadata: {"clawdbot":{"emoji":"🌐","requires":{"commands":["agent-browser"]},"homepage":"https://github.com/vercel-labs/agent-browser"}}
---

# Agent Browser Skill

Fast browser automation using accessibility tree snapshots with refs for deterministic element selection.

## Why Use This Over Built-in Browser Tool

**Use agent-browser when:**
- Automating multi-step workflows
- Need deterministic element selection
- Performance is critical
- Working with complex SPAs
- Need session isolation

**Use built-in browser tool when:**
- Need screenshots/PDFs for analysis
- Visual inspection required
- Browser extension integration needed

## Core Workflow

```bash
# 1. Navigate and snapshot
agent-browser open https://example.com
agent-browser snapshot -i --json

# 2. Parse refs from JSON, then interact
agent-browser click @e2
agent-browser fill @e3 "text"

# 3. Re-snapshot after page changes
agent-browser snapshot -i --json
```

## Key Commands

### Navigation
```bash
agent-browser open <url>
agent-browser back | forward | reload | close
```

### Snapshot (Always use -i --json)
```bash
agent-browser snapshot -i --json          # Interactive elements, JSON output
agent-browser snapshot -i -c -d 5 --json  # + compact, depth limit
agent-browser snapshot -s "#main" -i      # Scope to selector
```

### Interactions (Ref-based)
```bash
agent-browser click @e2
agent-browser fill @e3 "text"
agent-browser type @e3 "text"
agent-browser hover @e4
agent-browser check @e5 | uncheck @e5
agent-browser select @e6 "value"
agent-browser press "Enter"
agent-browser scroll down 500
agent-browser drag @e7 @e8
```

### Get Information
```bash
agent-browser get text @e1 --json
agent-browser get html @e2 --json
agent-browser get value @e3 --json
agent-browser get attr @e4 "href" --json
agent-browser get title --json
agent-browser get url --json
agent-browser get count ".item" --json
```

### Check State
```bash
agent-browser is visible @e2 --json
agent-browser is enabled @e3 --json
agent-browser is checked @e4 --json
```

### Wait
```bash
agent-browser wait @e2                    # Wait for element
agent-browser wait 1000                   # Wait ms
agent-browser wait --text "Welcome"       # Wait for text
agent-browser wait --url "**/dashboard"   # Wait for URL
agent-browser wait --load networkidle     # Wait for network
agent-browser wait --fn "window.ready === true"
```

### Sessions (Isolated Browsers)
```bash
agent-browser --session admin open site.com
agent-browser --session user open site.com
agent-browser session list
# Or via env: AGENT_BROWSER_SESSION=admin agent-browser ...
```

### State Persistence
```bash
agent-browser state save auth.json        # Save cookies/storage
agent-browser state load auth.json        # Load (skip login)
```

### Screenshots & PDFs
```bash
agent-browser screenshot page.png
agent-br

_meta.json

{
  "ownerId": "kn7amrtkn0tjk2r2yxf3hjgp0s7zn6g4",
  "slug": "agent-browser-clawdbot",
  "version": "0.1.0",
  "publishedAt": 1769032854381
}

skill-card.md

## Description:

Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection

This skill is ready for commercial/non-commercial use.

## Publisher:

[matrixy](https://clawhub.ai/user/matrixy)

### License/Terms of Use:


## Use Case:

Developers and agents use this skill to automate browser workflows through the agent-browser CLI, including navigation, accessibility snapshots, ref-based interactions, extraction, sessions, state persistence, screenshots, PDFs, and network controls.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Saved browser state, cookies, and localStorage can expose authenticated sessions or sensitive data.

Mitigation: Treat state files and storage output like credentials: do not commit, share, or log them, and prefer low-privilege test accounts for automation.

Risk: Global CLI installation can expand local execution and supply-chain exposure.

Mitigation: Install the CLI in an isolated environment and pin or verify the package version where possible.

Risk: Browser automation on logged-in sites can perform unintended actions if commands target the wrong page or session.

Mitigation: Use isolated sessions, re-snapshot after page changes, and review targets before executing actions against authenticated sites.

## Reference(s):

- [Agent Browser CLI homepage](https://github.com/vercel-labs/agent-browser)
- [ClawHub skill page](https://clawhub.ai/matrixy/skills/agent-browser-clawdbot)

## Skill Output:

**Output Type(s):** [text, markdown, shell commands, configuration guidance]

**Output Format:** [Markdown guidance with inline shell commands and JSON examples]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May produce browser state files, screenshots, PDFs, cookies, storage values, and extracted page data when the documented CLI commands are used.]

## Skill Version(s):

0.1.0 (source: server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

Sponsored

Ads related to Agent Browser and adjacent AI workflows.