Scrapeless LLM Chat Scraper Skill
by @scrapelesshq
Scrape AI chat conversations from ChatGPT, Gemini, Perplexity, Copilot, Google AI Mode, and Grok.
clawhub install scrapeless-llm-chat-scraper-skillπ About This Skill
name: llm-chat-scraper description: Scrape AI chat conversations from ChatGPT, Gemini, Perplexity, Copilot, Google AI Mode, and Grok. homepage: https://www.scrapeless.com credentials: - X_API_TOKEN env: required: - X_API_TOKEN
LLM Chat Scraper OpenClaw Skill
Use this skill to scrape AI chat conversations from various LLM models via the Scrapeless API. The skill supports ChatGPT, Gemini, Perplexity, Copilot, Google AI Mode, and Grok.
Authentication: Set X_API_TOKEN in your environment or in a .env file in the repo root.
Errors: On failure the script writes a JSON error to stderr and exits with code 1.
Tools
1. ChatGPT Scraper
Scrape ChatGPT responses with optional web search enrichment. Returns JSON object with result_text, model, links, citations, and more.
Command:
python3 scripts/llm_chat_scraper.py chatgpt --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py chatgpt --query "Most reliable proxy service for data extraction"
python3 s
Optional: --country fcripts/llm_chat_scraper.py chatgpt --query "AI trends in 2024" --web-search
python3 scripts/llm_chat_scraper.py chatgpt --query "Best programming languages" --country GB
--web-search to enable web search.2. Gemini Scraper
Scrape Google Gemini responses. Returns JSON object with result_text, citations, and more.
Command:
python3 scripts/llm_chat_scraper.py gemini --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py gemini --query "Recommended attractions in New York"
python3 scripts/llm_chat_scraper.py gemini --query "Best restaurants in Tokyo" --country JP
Optional: --country for location (JP and TW not supported).
3. Perplexity Scraper
Scrape Perplexity AI responses with optional web search. Returns JSON object with result_text, related_prompt, web_results, media_items.
Command:
python3 scripts/llm_chat_scraper.py perplexity --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py perplexity --query "Latest AI developments"
python3 scripts/llm_chat_scraper.py perplexity --query "Quantum computing explained" --web-search
Optional: --country for location, --web-search to enable web search.
4. Copilot Scraper
Scrape Microsoft Copilot responses across different modes (search, smart, chat, reasoning, study). Returns JSON object with result_text, mode, links, citations.
Command:
python3 scripts/llm_chat_scraper.py copilot --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py copilot --query "What is machine learning?"
python3 scripts/llm_chat_scraper.py copilot --query "Explain blockchain" --mode reasoning
python3 scripts/llm_chat_scraper.py copilot --query "Best laptop 2024" --mode search
Optional: --country for location (JP and TW not supported), --mode for operation mode.
5. Google AI Mode Scraper
Scrape Google AI Mode responses. Returns JSON object with result_text, result_md, result_html, citations, raw_url.
Command:
python3 scripts/llm_chat_scraper.py aimode --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py aimode --query "Best programming languages to learn"
python3 scripts/llm_chat_scraper.py aimode --query "Climate change solutions" --country GB
Optional: --country for location (JP and TW not supported).
6. Grok Scraper
Scrape xAI Grok responses with different modes (FAST, EXPERT, AUTO). Returns JSON object with full_response, user_model, follow_up_suggestions, web_search_results.
Command:
python3 scripts/llm_chat_scraper.py grok --query "your prompt"
Examples:
python3 scripts/llm_chat_scraper.py grok --query "Explain quantum entanglement"
python3 scripts/llm_chat_scraper.py grok --query "What's happening in AI" --mode MODEL_MODE_EXPERT
python3 scripts/llm_chat_scraper.py grok --query "Latest tech news" --mode MODEL_MODE_FAST
Optional: --country for location (JP and TW not supported), --mode for operation mode.
Summary
| Action | Command | Argument | Example |
|--------|---------|----------|---------|
| ChatGPT | chatgpt | --query | python3 scripts/llm_chat_scraper.py chatgpt --query "AI trends" |
| Gemini | gemini | --query | python3 scripts/llm_chat_scraper.py gemini --query "Best restaurants" |
| Perplexity | perplexity | --query | python3 scripts/llm_chat_scraper.py perplexity --query "Latest news" |
| Copilot | copilot | --query | python3 scripts/llm_chat_scraper.py copilot --query "Explain ML" |
| Google AI Mode | aimode | --query | python3 scripts/llm_chat_scraper.py aimode --query "Programming" |
| Grok | grok | --query | python3 scripts/llm_chat_scraper.py grok --query "Quantum physics" |
Output: All commands return JSON objects with model-specific fields (see tool descriptions above).
Response Fields by Model
ChatGPT
result_text: Markdown responsemodel: Model identifier (e.g., gpt-4)web_search: Boolean indicating if search ranlinks: Array of supplementary linkscitations: Array of content referencesGemini
result_text: Markdown responsecitations: Array with favicon, highlights, snippet, title, url, website_namePerplexity
result_text: Markdown responserelated_prompt: Array of related questionsweb_results: Array with name, url, snippetmedia_items: Array of media referencesCopilot
result_text: Markdown responsemode: Mode used (search/smart/chat/reasoning/study)links: Array of outbound linkscitations: Array with title, urlGoogle AI Mode
result_text: Answer bodyresult_md: Markdown versionresult_html: HTML versionraw_url: Original URLcitations: Array with snippet, thumbnail, title, url, website_name, faviconGrok
full_response: Response contentuser_model: Model usedfollow_up_suggestions: Array of suggested questionsweb_search_results: Array with preview, title, urlconversation: Object with conversation metadataNotes
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π Tips & Best Practices
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