Browser Automation Zero Token#

Use agent-browser plus OpenClaw skills to turn repeatable browser tasks into reusable, low-maintenance workflows.

When To Use#

Use this skill for repeatable browser workflows such as:

• daily site sign-in
• repeated login + click flows
• dashboard checks
• fixed form-filling routines
• internal admin flows

Prefer this pattern when Playwright/Puppeteer feels too heavy, selectors are brittle, or repeated screenshot/tool loops waste tokens.

Core Workflow#

Always think in this loop:

1. OPEN — open the target page
2. SNAPSHOT — inspect page structure and collect current @refs
3. INTERACT — click / fill / select using @refs
4. VERIFY — re-snapshot or check page state after each meaningful change
5. REPEAT — continue until the business task is done
6. CLOSE — close the browser session cleanly

Short form:

OPEN → SNAPSHOT → INTERACT → VERIFY → REPEAT → CLOSE

Preconditions#

Before using this skill, verify:

• agent-browser is installed
• browser runtime/dependencies are installed
• the target site allows normal browser interaction
• credentials are available if login is required
• the user is authorized to automate the target site

Install CLI:

bash

npm install -g agent-browser
agent-browser install --with-deps
agent-browser --version

Optional ecosystem install:

bash

clawhub install openclaw-skills-browserautomation-skill

Base Command Set#

Use this minimal loop:

bash

agent-browser open <url>
agent-browser snapshot -i
agent-browser click @e<n>
agent-browser fill @e<n> "text"
agent-browser state save auth.json
agent-browser state load auth.json
agent-browser close

Important rule: @refs come from the latest snapshot. After navigation or major DOM changes, snapshot again. More command notes live in references/source-notes.md.

Operating Rules#

1. Snapshot before interacting#

Do not guess refs. Always obtain fresh @refs from agent-browser snapshot -i before click/fill/select actions.

2. Re-snapshot after state changes#

After login, route changes, modal opens, tab switches, or dynamic content loads, run snapshot again.

3. Prefer refs over brittle selectors#

Use @e<n> from snapshots whenever possible. Fall back to complex selectors only when refs or semantic locators are insufficient.

4. Save auth state for recurring tasks#

If the workflow requires login and will be reused:

bash

agent-browser state save auth.json
agent-browser state load auth.json

This is often the difference between “semi-automated” and “truly one-command repeatable.”

5. Verify, don’t assume#

After key actions, confirm progress using one or more of:

• another snapshot
• agent-browser get url
• agent-browser get title
• visible text checks
• screenshots for debugging

Zero-Token Execution Pattern#

Use zero-token mode when the workflow is already known and stable:

1. discover the workflow once
2. capture the working CLI sequence
3. store it in a skill or task markdown
4. rerun it directly without repeated AI reasoning

Example:

bash

agent-browser open https://example.com/login
agent-browser snapshot -i
agent-browser fill @e3 "username"
agent-browser fill @e4 "password"
agent-browser click @e5
agent-browser snapshot -i
agent-browser click @e21
agent-browser close

Build A Reusable Site Skill#

When the user wants to turn one website flow into a reusable skill:

1. identify the business goal
2. map the page flow once
3. note where refs must be refreshed
4. decide whether auth state should be saved/loaded
5. write the repeatable steps into a concise skill
6. document failure points and re-snapshot requirements

A good site skill should capture:

• target site / task
• prerequisites
• ordered browser steps
• verification points
• state save/load strategy
• caveats about changing refs

Example: Daily Sign-In Flow#

md

---
name: auto-signin-example
description: Automatically sign in to example.com using agent-browser CLI.
---

# Auto Sign-In Example

## Workflow
1. Open the login page.
2. Snapshot interactive elements.
3. Fill username and password using current refs.
4. Click the login button.
5. Re-snapshot after navigation.
6. Click the sign-in button.
7. Save state if reuse is needed.
8. Close the browser.

Debugging#

If the automation breaks, check in this order:

1. was a fresh snapshot taken?
2. did the page navigate or re-render?
3. did login fail silently?
4. did the saved state expire?
5. did a ref change?
6. does the flow need an explicit wait?

For command examples, see references/source-notes.md.

When Not To Use This Pattern#

Avoid overcommitting to zero-token browser automation when:

• the task requires heavy judgment each run
• the page changes unpredictably every time
• anti-bot controls block normal automation
• the target workflow includes sensitive steps that should not be automated without explicit approval
• direct API integration would be cleaner and more reliable

References#

If you need the distilled source rationale, read references/source-notes.md.

Output Expectations#

Depending on the request, this skill should help produce one of:

• a repeatable CLI command sequence
• a site-specific automation skill
• a debugging checklist for a broken browser flow
• a saved-state based recurring automation routine

Common Failure Modes#

Avoid these:

• using stale refs after navigation
• storing hardcoded assumptions without verification steps
• skipping auth-state management for recurring tasks
• claiming zero-token while still relying on repeated AI interpretation each run

Fast Heuristic#

If the workflow can be discovered once, re-run many times, and verified through snapshots/state checks, it is a strong candidate for this skill.