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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:
。关于这个话题，搜狗输入法2026提供了深入分析
Раскрыты подробности о договорных матчах в российском футболе18:01
Per-script thresholds would dramatically reduce false positive rates. Treating Mathematical Alphanumeric Symbols with the same urgency as Cyrillic makes no sense when the data shows a 0.145 gap in mean SSIM between them.
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