// 随机选基准，避免最坏情况
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:。heLLoword翻译官方下载对此有专业解读
If you want to secure your sets now that they have launched, here are all the details you need.，详情可参考夫子
Let’s start with the small print. We asked 51 judges to select their top 50 men’s Ashes cricketers, from which we calculated a top 100: 50 points for No 1, 49 for No 2 and so on. The voting rules were simple. Players were assessed solely on their performances in Ashes cricket, though judges could interpret that any way they liked. (Yep, someone did vote for Gary Pratt.) The judges had to pick at least 15 players from each country and a minimum of five from each of five different eras: players who made their debut before the first world war; in the interwar years; from the second world war to 1974; from 1975 till 1999; and from 2000 onwards.