ACTION_ID: ai_web_navigator
NAME: Web Pilot
CATEGORY: enrich
CREDITS: 0

Navigate the browser step-by-step using Floqer. Use this when a
research task requires clicking, filling forms, or paging through a
site behind multi-step navigation — anything beyond a single-shot web
search.

INDEX:
  1. Inputs
  2. Outputs
  3. How to configure
  4. Key notes
  5. Where it fits in a workflow
  6. When to use
  7. When not to use

================================================================================
1. INPUTS
================================================================================

task (string, required)
  Task. Step-by-step plan for browser navigation.

================================================================================
2. OUTPUTS
================================================================================

final_result (string) — Final Result. Placeholder: "XYZ is a B2B
  company".
steps_taken (jsonArray) — Steps Taken.
time_taken_seconds (number) — Time Taken (seconds). Placeholder: 0.
run_id (string) — Run Id.

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3. HOW TO CONFIGURE
================================================================================

Configure Action body:

{
  "inputs": {
    "task": "Open https://example.com, click the 'Pricing' link, and return the price of the Pro plan."
  }
}

Field-by-field:
  - task   Free-text step-by-step plan describing what the browser
           agent should do. `{{ref}}` tokens (e.g.
           `{{input.company_website}}`) resolve per row, so every row
           runs its own navigation.

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4. KEY NOTES
================================================================================

- One run per row. The `task` text resolves with that row's
  `{{ref}}` values, the agent navigates, and the result lands on the
  row.
- The `final_result` output is free text. If you need a structured
  shape downstream, follow with `llm_models` (with `output_format`)
  or `format_data_using_js_expression` to extract typed fields.
- Slower and more expensive per row than `llm_web_agents` — only
  reach for this when actual browser interaction is required.

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5. WHERE IT FITS IN A WORKFLOW
================================================================================

Pattern: account list -> ai_web_navigator (step-by-step web nav) ->
llm_models (extract / structure the final_result) -> downstream.

================================================================================
6. WHEN TO USE
================================================================================

Use ai_web_navigator for step-by-step browser tasks (filling forms,
navigating multi-page sites, scraping behind logins, paging through
results).

================================================================================
7. WHEN NOT TO USE
================================================================================

Need single-shot web research with citations (no clicking)
  -> llm_web_agents
     (https://floqer.com/docs/action-detail/llm_web_agents.txt)

Need to scrape a single known URL
  -> scrape_web_page_using_firecrawl
     (https://floqer.com/docs/action-detail/scrape_web_page_using_firecrawl.txt)

================================================================================

This file is maintained manually. Last updated: 2026-04-30.
Full interactive reference: https://floqer.com/docs/reference
Action catalog: https://floqer.com/docs/action-catalog.txt