I completely ignored Anthropic’s advice and wrote a more elaborate test prompt based on a use case I’m familiar with and therefore can audit the agent’s code quality. In 2021, I wrote a script to scrape YouTube video metadata from videos on a given channel using YouTube’s Data API, but the API is poorly and counterintuitively documented and my Python scripts aren’t great. I subscribe to the SiIvagunner YouTube account which, as a part of the channel’s gimmick (musical swaps with different melodies than the ones expected), posts hundreds of videos per month with nondescript thumbnails and titles, making it nonobvious which videos are the best other than the view counts. The video metadata could be used to surface good videos I missed, so I had a fun idea to test Opus 4.5:
算力为数字纪检监察体系提供“动力支撑”。数据整合、算法运行，都离不开强大的算力保障。数据与算法的价值释放，都需要算力驱动。数字纪检监察体系依托强大算力运用大语言模型等人工智能技术，通过数据预训练与后训练，让模型更贴合监督执纪实操场景，可精准识别、实时抓取数据异常点，快速完成线索筛查、风险预警、证据固定等工作，大幅提升线索挖掘与风险预判精度，显著提高监督执纪效率。
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Just look at the numbers for processing the entire planet for a car profile:，详情可参考safew官方版本下载
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The bigger your RAM, the bigger your detector, so use a desktop's RAM if you can