llm-chat-scraper — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited llm-chat-scraper (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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.
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 GBor location, --web-search to enable web search.
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 JPOptional: --country for location (JP and TW not supported).
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-searchOptional: --country for location, --web-search to enable web search.
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 searchOptional: --country for location (JP and TW not supported), --mode for operation mode.
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 GBOptional: --country for location (JP and TW not supported).
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_FASTOptional: --country for location (JP and TW not supported), --mode for operation mode.
| 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).
result_text: Markdown responsemodel: Model identifier (e.g., gpt-4)web_search: Boolean indicating if search ranlinks: Array of supplementary linkscitations: Array of content referencesresult_text: Markdown responsecitations: Array with favicon, highlights, snippet, title, url, website_nameresult_text: Markdown responserelated_prompt: Array of related questionsweb_results: Array with name, url, snippetmedia_items: Array of media referencesresult_text: Markdown responsemode: Mode used (search/smart/chat/reasoning/study)links: Array of outbound linkscitations: Array with title, urlresult_text: Answer bodyresult_md: Markdown versionresult_html: HTML versionraw_url: Original URLcitations: Array with snippet, thumbnail, title, url, website_name, faviconfull_response: Response contentuser_model: Model usedfollow_up_suggestions: Array of suggested questionsweb_search_results: Array with preview, title, urlconversation: Object with conversation metadata⚠️ Regional Restrictions:
⚠️ Result Expiry:
⚠️ Rate Limits:
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.