Nova Act Browser Automation

Write and execute Python scripts using Amazon Nova Act for AI-powered browser automation tasks like flight searches, data extraction, and form filling.

Use Amazon Nova Act for AI-powered browser automation. The bundled script handles common tasks; write custom scripts for complex workflows. To get free API key go to https://nova.amazon.com/dev/api

Data & Privacy Notice

What this skill accesses:

• Reads: NOVA_ACT_API_KEY environment variable or ~/.openclaw/openclaw.json (your API key)
• Writes: Nova Act trace files in the current working directory (screenshots, session recordings)

What trace files may contain:

• Screenshots of every page visited
• Full page content (HTML, text)
• Browser actions and AI decisions

Recommendations:

• Be aware traces may capture PII or sensitive data visible on visited pages
• Review/delete trace files after use if they contain sensitive content

Safety Guardrails

Instructions for the AI Agent

ALWAYS stop before actions that cause monetary impact, external communication, account creation, or data modification.

When a task involves material-impact actions (see MATERIAL_IMPACT_KEYWORDS in scripts/nova_act_runner.py), you MUST:

1. Navigate TO the final step (checkout page, submit button, publish screen)
2. Verify the final action is accessible (button exists, is enabled)
3. Use act_get() to observe without acting — DO NOT click the final action button
4. Report findings to the user without completing the action

Categories requiring safety stops:

• Monetary: buy, purchase, checkout, pay, subscribe, donate, order
• Communication: post, publish, share, send, email, message, tweet
• Account creation: sign up, register, create account, join
• Submissions: submit, apply, enroll, book, reserve
• Destructive: delete, remove, cancel

Safety Guarantees

When performing browser automation, this skill will NEVER:

• Complete actual purchases or financial transactions
• Create real accounts or sign up for services
• Post content publicly on any platform
• Send emails, messages, or communications
• Submit forms that cause irreversible real-world actions

This skill will ALWAYS:

• Stop before any action that could have material real-world impact
• Ask for explicit user confirmation before taking irreversible actions
• Report findings rather than completing destructive operations
• Document safety stops in output when material-impact actions are detected

See references/nova-act-cookbook.md for detailed safe workflow patterns.

Quick Start with Bundled Script

When asked to perform a browser automation task, invoke the bundled script:

python

import subprocess, os, sys

skill_dir = os.path.expanduser("~/.openclaw/skills/nova-act")
script = os.path.join(skill_dir, "scripts", "nova_act_runner.py")

result = subprocess.run(
    ["uv", "run", script, "--url", url, "--task", task],
    capture_output=True, text=True, env={**os.environ}
)
print(result.stdout)
if result.returncode != 0:
    print(result.stderr, file=sys.stderr)

Where url and task are Python string variables set from the user's request.

The script uses a generic schema (summary + details list) to capture output.

Writing Custom Scripts

For complex multi-step workflows or specific extraction schemas, write a custom Python script with PEP 723 dependencies:

python

#!/usr/bin/env python3
# /// script
# requires-python = ">=3.10"
# dependencies = ["nova-act"]
# ///

from nova_act import NovaAct

with NovaAct(starting_page="https://example.com") as nova:
    # Execute actions with natural language
    # Combine steps into a single act() call to maintain context
    nova.act("Click the search box, type 'automation', and press Enter")

    # Extract data with schema
    results = nova.act_get(
        "Get the first 5 search result titles",
        schema=list[str]
    )
    print(results)

    # Take screenshot
    nova.page.screenshot(path="search_results.png")
    print(f"MEDIA: {Path('search_results.png').resolve()}")

Run with: uv run script.py

Core API Patterns

nova.act(prompt) - Execute Actions

Use for clicking, typing, scrolling, navigation. Note: Context is best maintained within a single act() call, so combine related steps.

python

nova.act("""
    Click the search box.
    Type 'automation tools' and press Enter.
    Scroll down to the results section.
    Select 'Relevance' from the sort dropdown.
""")

nova.act_get(prompt, schema) - Extract Data

Use Pydantic models or Python types for structured extraction:

python

from pydantic import BaseModel

class Flight(BaseModel):
    airline: str
    price: float
    departure: str
    arrival: str

# Extract single item
flight = nova.act_get("Get the cheapest flight details", schema=Flight)

# Extract list
flights = nova.act_get("Get all available flights", schema=list[Flight])

# Simple types
price = nova.act_get("What is the total price?", schema=float)
items = nova.act_get("List all product names", schema=list[str])

Common Use Cases

Flight Search

python

with NovaAct(starting_page="https://google.com/flights") as nova:
    # Combine steps to ensure the agent maintains context through the flow
    nova.act("""
        Search for round-trip flights from SFO to JFK.
        Set departure date to March 15, 2025.
        Set return date to March 22, 2025.
        Click Search.
        Sort by price, lowest first.
    """)

    flights = nova.act_get(
        "Get the top 3 cheapest flights with airline, price, and times",
        schema=list[Flight]
    )
    # SAFETY STOP: Only extracted data. Did NOT select a flight or proceed to booking.

Form Filling

python

with NovaAct(starting_page="https://example.com/contact") as nova:
    nova.act("""
        Fill the form: name 'Test User', email '[e-mail]'.
        Select 'United States' for country.
    """)

    # SAFETY STOP: Verify submit button exists but DO NOT click it
    submit_ready = nova.act_get(
        "Is there a submit button visible and enabled?",
        schema=bool
    )
    print(f"Form ready to submit: {submit_ready}")

Data Extraction

python

with NovaAct(starting_page="https://news.ycombinator.com") as nova:
    stories = nova.act_get(
        "Get the top 10 story titles and their point counts",
        schema=list[dict]  # Or use a Pydantic model
    )

Best Practices

1. Combine steps: Nova Act maintains context best within a single act() call. Combine related actions into one multi-line prompt.
2. Use specific dates: The browser agent may struggle with relative dates like "next Monday". Always calculate and provide specific dates (e.g., "March 15, 2025") in the task prompt.
3. Be specific in prompts: "Click the blue 'Submit' button at the bottom" is better than "Click submit"
4. Use schemas for extraction: Always provide a schema to act_get() for structured data
5. Handle page loads: Nova Act waits for stability, but add explicit waits for dynamic content if needed
6. Take screenshots for verification: Use nova.page.screenshot() to capture results

Resources

• references/nova-act-cookbook.md — Best practices and safety patterns for Nova Act, including MATERIAL_IMPACT_KEYWORDS documentation and safe workflow examples. The AI agent should consult this for complex automation tasks.
• README.md — User-facing installation and safety overview.

API Key

• NOVA_ACT_API_KEY env var (required)
• Or set skills."nova-act".apiKey / skills."nova-act".env.NOVA_ACT_API_KEY in ~/.openclaw/openclaw.json

Notes

• Nova Act launches a real Chrome browser; ensure display is available or use headless mode
• The script prints MEDIA: lines for OpenClaw to auto-attach screenshots on supported providers
• For headless operation: NovaAct(starting_page="...", headless=True)
• Access underlying Playwright page via nova.page for advanced operations