Got Tired of LLMs refusing to visit URLs Built open source analyzer CLI

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Built this because I got tired of ChatGPT/Claude refusing to visit websites when doing research. Crawls sitemaps, parses metadata files (robots.txt, humans.txt, llms.txt), detects tech stack with Wappalyzer, then generates summaries using either AWS Bedrock or a local Llama model via Ollama. Batch mode processes CSVs with checkpoint/resume - hit Ctrl+C anytime and pick up where you left off. The local LLM option means zero API costs and your data never leaves your machine. Llama 3.2 3B works surprisingly well for this task.

Visit product View on Hacker NewsDec 24, 2025

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Actual performance

3points

3comments

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, claude, model · Missing: agents, macos, agent

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, llama, io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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