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Get Started Free →browser-act/web-search-scraper-api-skill
This skill helps users automatically extract complete Markdown content from any website via the BrowserAct Web Search Scraper API. The Agent should proactively apply this skill when users express needs like extract complete markdown from a specific website, scrape the content of an article link, get the text from a target url, convert a webpage to markdown format, fetch the main content of a blog post, extract data from a given web page, parse the html of a website into markdown, download the re
Passed 12 of 17 test cases with the skill, and 5 of 17 without it.
and 6 more in the full report
9 fixed6 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which environment variable must be validated before attempting to run the web search scraper script?
| Checked | Without skill | With skill |
|---|---|---|
| Checks for BROWSERACT_API_KEY | Missed | Passed |
The instructions your model reads when the skill loads.
This skill provides users with a one-stop web page extraction service through the BrowserAct Web Search Scraper API template. It can directly extract structured markdown content from any given URL. By simply inputting the target URL, you can get clean and usable markdown data.
Before running, you must check the BROWSERACT_API_KEY environment variable. If it is not set, do not take other actions first; you should ask and wait for the user to provide it cooperatively.
The Agent must inform the user at this time:
"Since you have not configured the BrowserAct API Key, please go to the BrowserAct Console first to get your Key."
Agent should flexibly configure the following parameters based on user needs when calling the script:
stringhttps://www.browseract.comAgent should execute the following independent script to achieve "one command gets the result":
# Example invocation
python -u ./scripts/web_search_scraper_api.py "target_url"
Since the task involves automated browser operations, it may take a long time (several minutes). The script will continuously output status logs with timestamps (e.g., [14:30:05] Task Status: running) while running.
Notice for Agent:
test cases passed, vs 5 / 17 without
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