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  "text": "兄弟們,你現在可以把任何視頻蒸留成Skills了。\n我這兩天拿吳文達那門2026年的給所有人的AI入門課稍微淺淺地嘗試了一下。\n26個視頻,整整4個多小時,讓他從視頻一路跑到Skills差不多用了一個小時。\n最後拿出來的是25個Agent可以直接調用的Skills。\n這個結果讓我說實話,屬實有點超乎我的預期。\n因為倉頡Skills這個項目,我也才今年4月份才開源。\n最開始做它的時候,想法其實也挺簡單的。\n我不是想做一個多大的系統,就是被一個問題卡住了。\nAI能不能真的拆書?\n不是把一本書總結成幾條金句,而是把書裡的方法、步驟、判斷標準拆出來。\n變成後面Agent能用的東西。\n所以第一版基本圍繞拆書來做。\n開源之後,我也沒怎麼宣傳,就放在那裡。\n結果兩個多月過去,慢慢長到了1.3K star,長得不算特別快。\n但對我來說,已經夠說明問題了。\n尤其是issue裡,不斷有人問,能不能支持視頻,支持播客?\n還能不能處理課程?\n這些問題看多了,我才意識到,大家要的可能不是一個普通的工具。\n而是一個能把長內容變成方法論的全新生產力工具。\n所以這次2.0,我就把範圍放開了。\n現在可以處理長視頻、課程、播客、訪談。\n只要裡面有方法論,其實也可以是。\n這裡我想強調一個區別。\n總結和蒸留不是一回事。\n總結是告訴你,這個內容講了什麼。\n蒸留是把裡面真正能復用的東西拆出來。\n比如判斷框架、操作步驟、注意事項、還有一些適用邊界等等。\n所以這些東西拆出來之後,Agent後面才有可能在別的任務裡繼續調用。\n這次的流程大概是這樣。\n你可以先輸入視頻鏈接,然後下載視頻、提取音頻、轉成文字。\n再把文字交給倉頡Skill做蒸留,最後生成Skill。\n我沒有把視頻處理,直接塞進倉頡Skill。\n這個地方我糾結過,但最後還是拆開了。\n因為一旦把下載、轉寫、音頻處理都放進去,倉頡Skill會越來越重。\n但其實它最核心的能力還是文本蒸留。\n所以視頻這部分,我單獨做成了一個Video-to-Text Skill。\n一個負責把視頻變成文字,另一個負責把文字變成Skill。\n這樣反而清楚一點。\n溫達這門課是我拿來跑的第一個完整測試。\n用Longland GCAT2.0加Cloud Code,完整跑下來大概一個小時,除了25個Skill。\n第二個測試是YouTube上四個講Loop Engineering的視頻。\n總時長80多分鐘,最後蒸留出了8個Skill。\n跑完之後,我沒有馬上停,我又追問了幾個問題。\n比如Loop Engineering,到底是什麼?\n它適不適合用來優化APP,到底能不能拿來做內容創作?\n結果它給的回答還挺具體,不是那種可以提升效率、優化流程的套話。\n它會告訴我哪些場景適合,哪些地方容易誤用,應該怎麼拆步驟。\n這點讓我有點意外。\n我原以為蒸留出來的Skill最多就是方便以後查一下。\n但追問幾輪之後,我發現它真的能繼續參與判斷。\n這也是我這次測試最大的收穫。\n倉頡Skill可能不只是一個AI拆書工具。\n它更像是一個把長內容變成Agent能力模塊的工具。\n書可以,你買的課程可以。\n只要長視頻、播客、訪談等等這些,裡面有結構、有方法、有經驗,都可以試著蒸留。\nVideo.to.skill我也已經開源了。\n感興趣的話可以去倉庫裡看一下。\n我是袋鼠帝,一個繼續折騰AI生產力工具的人。\n我們下期見。",
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      "text": "兄弟們,你現在可以把任何視頻蒸留成Skills了。",
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      "text": "26個視頻,整整4個多小時,讓他從視頻一路跑到Skills差不多用了一個小時。",
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      "text": "我不是想做一個多大的系統,就是被一個問題卡住了。",
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      "text": "AI能不能真的拆書?",
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      "text": "不是把一本書總結成幾條金句,而是把書裡的方法、步驟、判斷標準拆出來。",
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      "text": "變成後面Agent能用的東西。",
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      "text": "所以第一版基本圍繞拆書來做。",
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      "text": "開源之後,我也沒怎麼宣傳,就放在那裡。",
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      "text": "結果兩個多月過去,慢慢長到了1.3K star,長得不算特別快。",
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      "text": "但對我來說,已經夠說明問題了。",
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      "text": "尤其是issue裡,不斷有人問,能不能支持視頻,支持播客?",
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      "text": "這些問題看多了,我才意識到,大家要的可能不是一個普通的工具。",
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      "text": "只要裡面有方法論,其實也可以是。",
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      "text": "這裡我想強調一個區別。",
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      "text": "總結和蒸留不是一回事。",
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      "text": "總結是告訴你,這個內容講了什麼。",
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      "text": "蒸留是把裡面真正能復用的東西拆出來。",
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      "text": "比如判斷框架、操作步驟、注意事項、還有一些適用邊界等等。",
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      "text": "所以這些東西拆出來之後,Agent後面才有可能在別的任務裡繼續調用。",
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      "text": "這次的流程大概是這樣。",
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      "text": "你可以先輸入視頻鏈接,然後下載視頻、提取音頻、轉成文字。",
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      "text": "再把文字交給倉頡Skill做蒸留,最後生成Skill。",
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      "text": "我沒有把視頻處理,直接塞進倉頡Skill。",
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      "text": "這個地方我糾結過,但最後還是拆開了。",
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      "text": "因為一旦把下載、轉寫、音頻處理都放進去,倉頡Skill會越來越重。",
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      "text": "但其實它最核心的能力還是文本蒸留。",
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      "text": "所以視頻這部分,我單獨做成了一個Video-to-Text Skill。",
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      "text": "一個負責把視頻變成文字,另一個負責把文字變成Skill。",
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      "text": "這樣反而清楚一點。",
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      "text": "溫達這門課是我拿來跑的第一個完整測試。",
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      "text": "用Longland GCAT2.0加Cloud Code,完整跑下來大概一個小時,除了25個Skill。",
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      "text": "第二個測試是YouTube上四個講Loop Engineering的視頻。",
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      "text": "總時長80多分鐘,最後蒸留出了8個Skill。",
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      "text": "跑完之後,我沒有馬上停,我又追問了幾個問題。",
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      "text": "比如Loop Engineering,到底是什麼?",
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      "text": "它適不適合用來優化APP,到底能不能拿來做內容創作?",
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      "text": "結果它給的回答還挺具體,不是那種可以提升效率、優化流程的套話。",
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      "text_original": "結果它給的回答還挺具體,不是那種可以提升效率、優化流程的套化。",
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      "text": "它會告訴我哪些場景適合,哪些地方容易誤用,應該怎麼拆步驟。",
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      "text": "這點讓我有點意外。",
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      "text": "這也是我這次測試最大的收穫。",
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      "text": "倉頡Skill可能不只是一個AI拆書工具。",
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      "text": "它更像是一個把長內容變成Agent能力模塊的工具。",
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      "text": "書可以,你買的課程可以。",
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      "text": "只要長視頻、播客、訪談等等這些,裡面有結構、有方法、有經驗,都可以試著蒸留。",
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      "text": "Video.to.skill我也已經開源了。",
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      "text": "感興趣的話可以去倉庫裡看一下。",
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      "text": "我是袋鼠帝,一個繼續折騰AI生產力工具的人。",
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      "text": "我們下期見。",
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