Tag: claude-code
All the articles with the tag "claude-code".
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Claude Code 週年對話的幾個重點
Claude Code 滿一歲，光頭與吳貓釋出一段週年對話。整理幾個核心重點：Agent 軍團化、自動模式與常規任務、職能融合與行動辦公、脈絡極簡主義。
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別把上一個對話的 JSON 餵給它，先體檢 harness
不必把上一個對話的上下文 JSON 整包餵進去：harness 有好幾種，AGENTS.md、rule、skill、hook 都能分擔，純 session history 含太多無用的 tool call。
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Worried About Agents Going Rogue? Start Isolated, Hand Off Gradually
Someone asked what to do if you worry about AI agents going rogue. My answer: don't pick a highly autonomous lobster up front. Start in an isolated setting where you supervise and approve every step, then let go slowly.
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A Few Months With Claude Code: The Companion Tools and Resources I've Accumulated
Pulling together what had been scattered across my micro-notes: ccusage for costs, claude-log-cli for finding old conversations, how-claude-code-works for systematic understanding, plus the Claude Extension I pair with it daily.
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Claude Code To-Do Tiering: Auto / Review / Collaborate / Manual
A small discovery from using Claude Code: sort to-dos by repo, then into four tiers — auto, review, collaborate, manual. Stuff that used to drag on all day now finishes in an hour.
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The Day Opus 4.8 Went Haywire: tool call cannot be parsed
A one-day timeline from 2026-06-02: from hopping on X for moral support, to someone finally pinning down the root cause of tool call cannot be parsed.
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I Built a "Tinghao SKILL" — Distilling a Finance YouTuber's Perspective Into AI
I spent my leftover Claude quota building a Tinghao SKILL: 17 finance episodes distilled, 3-4 rounds of blind testing, and a curious difference in how AI and humans deploy dirty jokes.
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擔心 agent 失控？先在隔離環境逐步放手
有人問擔心 AI agent 失控怎麼辦。我的回覆是：別一開始就選高度自主的龍蝦，先在你親自監督放行每一步的隔離環境裡操作，再慢慢放手。
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用 Claude Code 這幾個月，累積下來的周邊工具與學習資源
把這幾個月散落在碎念裡的東西整理成一篇：看成本的 ccusage、查歷史對話的 claude-log-cli、系統性理解的 how-claude-code-works，再加上日常搭配的 Claude Extension。
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Claude Code 待辦分級制：自動／審核／協作／手動四級分流
一個用 Claude Code 的小發現：把待辦先分 repo 再分成自動／審核／協作／手動四級，原本拖一整天的事 1 小時內就做完了。
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Opus 4.8 全線抽風的一天：tool call cannot be parsed
2026-06-02 一整天的事件線：從上 X 抱團取暖，到 tool call cannot be parsed 的根因被人找出來。
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我做了一個「庭皓 SKILL」——把財經 YouTuber 的觀點蒸餾成 AI
用沒燒完的閒 token 做了一個庭皓 SKILL：蒸餾 17 部財經速解讀、3-4 輪盲測驗證，還發現 AI 跟人類講黃段子的邏輯不太一樣。
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The Blind Spot in AI Self-Verification — Why You Need an Uninformed Agent to Audit
AI is great at "looking done." To catch its blind spots, you can't rely on it checking its own work — you bring in an auditor that knows nothing, inherits no context, and gets only the rules and the output.
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AI 自我驗證的盲點——為什麼要請一個不知情的 agent 來稽核
AI 很會「看起來完成了」。要抓出它的盲點，不能靠它自己回頭檢查——得引入一個不知情、不繼承上下文、只拿到原則與產出的稽核者。
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Better Context Beats a Stronger Model — repowise's Five-Layer Architecture
I came across repowise, a tool that inserts a layer of context between your codebase and the model. It is a good excuse to talk about a bigger idea: when a model breaks things, the first instinct is to reach for a stronger model, but the real cause is usually too little context.
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給 LLM 更好的 context，勝過換更強的模型——repowise 的五層架構
看到 repowise 這個在 codebase 與模型之間插一層 context 的工具，想聊一個更大的觀念：模型改壞東西時，第一反應常常是換更強的模型，但真正的根因往往是 context 不夠。
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A Student's Seven-Agent Setup That Wouldn't Run — A Cautionary Tale About Harness First
A student built seven agents on an M5 Max and kept hitting timeouts. The problem wasn't a weak model — it was skipping the basics: harness, context management, task routing.
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學員自建七個 agent 跑不動——一個 harness 為重的反面教材
一個學員在 M5 Max 上自建七個 agent 卻一直 timeout，問題不在模型不夠強，而在沒先把 harness、上下文管理、任務分派這些基本功打好。
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Love-Hate With Anthropic — Sneering at the Elitism While Devouring Their Engineering Blog
I have a love-hate thing with Anthropic: I hate the smug elitism and the black-box token-burning, but their engineering blog is some of the best out there, especially the security and permissions stuff.
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又愛又恨 Anthropic——一邊嫌精英心態，一邊狂讀他們的技術部落格
我對 Anthropic 又愛又恨：恨那股噁心的精英心態跟燒 token 的黑箱操作，愛他們數一數二高品質的技術部落格，尤其資安權限那塊。
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Racing for the Fastest Summary — Opus 4.8's 244-Page System Card, and How I Read It With 20 Agents in Half an Hour
The night Opus 4.8 launched, I split the 244-page system card into 20 chunks, handed them to 20 gemini agents to summarize in parallel, and pieced together the fastest rundown online. Plus a digest of Reddit's hands-on reactions within two hours of launch.
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拼全網最速——Opus 4.8 系統卡 244 頁重點，外加我怎麼用 20 個 agent 半小時讀完
Opus 4.8 發布當晚，我把 244 頁系統卡切成 20 份、丟給 20 個 gemini agent 並行摘要，拼出全網最速重點。附上發布兩小時內的 Reddit 實測整理。
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Claude Code Ecosystem Overview — Skills, Hooks, Agents in Full Bloom
Claude Code's ecosystem has grown from a simple CLI tool into a full platform: Skills supported across providers, Hooks intercepting commands, Agent View for multi-session management, and fork subagents with context inheritance.
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Claude Code 生態系盤點——Skill、Hook、Agent 全面開花
Claude Code 的生態系已經從單純的 CLI 工具長成一個完整的平台：Skill 各家都支援、Hook 攔截指令、Agent View 多工管理、fork subagent 繼承上下文。連社群都開始用 Skill 搞創意了。
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Running Claude Code on iPad — tmux + Tailscale + Moshi Setup Guide
A complete setup for running Claude Code on an iPad 11-inch: tmux for persistent sessions, Tailscale for NAT traversal, and Moshi as the SSH terminal. The goal is rebuilding 90% productivity, not just fixing bugs.
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iPad 跑 Claude Code 全攻略——tmux + Tailscale + Moshi
用 iPad 11 吋成功運行 Claude Code 的完整方案：tmux 保持 session、Tailscale 穿 NAT、Moshi 做 SSH 終端。目標是重建九成生產力，不只是修 bug。
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Cross-Model Review — Stop Letting AI Grade Its Own Homework
AI reviewing its own output has inherent blind spots. Using Codex for independent review or the Review Council skill to orchestrate a three-model expert team is the most pragmatic solution right now.
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跨模型互審——讓 AI 不再自己審自己
AI 自己審查自己的產出，盲點難以避免。用 Codex 做獨立審查、或用 Review Council skill 組三模型 expert team，是目前最務實的解法。
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Have Claude scan an MCP before you install it—it found 7 vulnerabilities and still said it's safe to install
This week AgentCrew Academy shipped a video about why you should run /security-scan before installing any MCP / npm / pip package. Tested a third-party MCP, Claude flagged 7 findings, then said "install is fine." This is the written companion to the video.
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裝 MCP 之前先讓 Claude 幫你掃——找到 7 個漏洞，但說這個可以裝
講座當週我拍了一支影片，講「裝任何 MCP / npm / pip / clone 之前先跑 /security-scan」這件事。實測了一個三方 MCP，Claude 掃出 7 個漏洞，但綜合評估後說「可以裝」。這篇是影片的補充文字版。
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Three moves to firepower-demo Agentic AI at your company—desktop cleanup, conflicting meeting notes, multi-version emails
If you want to make your manager or coworkers feel Agentic AI in one second—and then open the door to an internal training engagement—my three go-to moves are cleaning up messy desktops, reconciling conflicting meeting notes and emails, and producing multi-version drafts for different recipients. These three hit office workers right in the pain.
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在公司火力展示 Agentic AI 的三招——桌面整理、會議紀錄、信件多版本
想在公司讓主管同事一秒有感、進而開內訓案的話，我自己最常用的三招是：整理桌面亂檔、整理相互衝突的會議紀錄跟信件、迅速生成不同版本的信件給主管同事客戶廠商。這三招對辦公室的人就夠有感了。
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Covey's time management matrix, now with Claude Code—how each quadrant shifts
Covey's time management matrix from The 7 Habits of Highly Effective People splits time on two axes: important × urgent. Drop Claude Code into the picture and each quadrant's time allocation shifts. The long-term compounding from AI isn't in Q1, it's in Q2.
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Covey 七個習慣的時間矩陣放上 Claude Code 之後——每一格的時間分配怎麼變
Covey《高效能人士的七個習慣》的時間矩陣是兩軸切四象限，重要 × 緊急。把 Claude Code 放進去之後，每一格的時間分配會被重新洗牌。Q1/Q3 被 AI 吃掉，多出來的時間搬到 Q2 才是 AI 協作的長期複利。
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Two MCP servers for Taiwan public data—what mcp-taiwan-legal-db and Twinkle Hub are each good for
Two MCP servers wrapping Taiwan's public data sources—one focused on court judgments and statutes, the other aggregating 52,960 government open datasets plus 37 local utility tools. They turn out to be complementary; I now run both.
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台灣公開資料兩個 MCP 評測——mcp-taiwan-legal-db 跟 Twinkle Hub 各適合什麼場景
兩個串接台灣公開資料的 MCP server——一個專精法律判決跟法規查詢、一個聚合 5.3 萬筆政府開放資料 + 37 個在地工具。實測下來各有強項，課程跟導入場景的搭配方式不一樣。
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How to tune Opus 4.7's effort, and why I still keep non-coding tasks on Sonnet 4.6 medium
Opus 4.7's default adaptive effort is a disaster—it turns into a lazy emperor. You have to crank it up to high or xhigh to avoid that, but token consumption goes nuts. After testing, Sonnet 4.6 medium is the sweet spot for non-coding work.
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Opus 4.7 的 effort 怎麼調，跟為什麼我非編程任務還是停在 Sonnet 4.6 medium
Opus 4.7 預設的 adaptive effort 是場災難，會變成偷懶摸魚皇帝。要開到 high 或 xhigh 才能避免，但 token 就開始狂燒。實測下來，非編程任務停在 Sonnet 4.6 medium 反而是最好的選擇。
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Claude Code Desktop vs CLI right now—why I think beginners should just start with the desktop app
Two or three weeks ago Anthropic overhauled the desktop app. Over 90% of the features now match the CLI. If you're a beginner who's scared of the terminal, starting with the desktop app is fine.
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Claude Code 桌面版跟終端機現在差在哪——我為什麼覺得初學者直接從桌面版開始就好
兩三週前 Anthropic 把桌面 App 大翻新，90% 以上功能跟終端機同步。初學者對終端機有恐懼，現在從桌面版開始完全沒問題。
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Judging AI Risk on Two Axes: Reversibility × Environment Isolation
A common question in corporate trainings — "can I let AI do this automatically?" I answer with two axes: reversible vs irreversible, isolated vs production. This 2x2 prevents more incidents than any prompt-engineering tutorial.
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判斷 AI 風險的兩個維度：可逆性 × 環境隔離
企業內訓裡常被問的一題——「我可以讓 AI 自動做這件事嗎？」我用兩個維度回答：可逆 vs 不可逆、隔離環境 vs 生產環境。這個 2x2 矩陣比任何 prompt 教學都更能避免事故。
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Moving from Claude Code to Codex: I Built a Skill to Handle It
Migrating an entire personal harness from Claude Code to Codex is not trivial — claude.md / agents.md, MCP, hooks, settings each need their own translation. I packaged the workflow as a Skill on GitHub. Plus a note on why I keep reaching for Codex these days.
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從 Claude Code 搬家到 Codex：我做了一個 Skill 自動處理
把整套個人 harness 從 Claude Code 遷移到 Codex 不容易——claude.md / agents.md、MCP、hooks、settings 各自要對齊。我把流程包成一個 Skill 放在 GitHub，順便聊聊為什麼最近越來越常用 Codex。
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Is your AI subscription worth it? A night market steak framework
A $7 night market steak versus a $70 restaurant steak — the expensive one isn't ten times better. AI subscriptions work the same way. A framework for deciding whether you're actually getting value.
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AI 訂閱費值不值？夜市牛排思考框架
兩百塊夜市牛排 vs 兩千塊餐廳牛排，差十倍的價格未必差十倍的體驗。AI 訂閱也一樣。一個判斷 AI 訂閱費有沒有在「賺」的框架。
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Teaching non-technical people AI: five things the tech world assumes everyone knows
One student was a seasoned HR consultant who managed all her files across several USB drives and had never heard of an API. Here are five knowledge gaps that show up constantly when teaching AI tools outside the tech world — and what actually works.
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帶麻瓜學 AI：技術圈習以為常、但他們從來不知道的五件事
一位企業人資顧問、USB 隨身碟管理所有檔案、從來不知道 API 是什麼。這是在技術圈外推廣 AI 工具時，你會真實碰到的起點。五個知識落差，以及我現場用的方法。
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AI community digest W18: Claude detects Codex cheating, GPT 5.5 guardrails confuse everyone
Reddit AI community top posts from 4/28–4/29: r/ClaudeAI agent safety concerns, r/ChatGPT's GPT 5.5 content policy drama, r/LocalLLaMA on local model benchmarks, and Anthropic announcing Claude for Creative Work.
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AI 社群週報 W18：Claude 偵測到你在偷用 Codex、GPT 5.5 的過濾器到底鬆了沒
4/28–4/29 的 Reddit AI 社群熱門話題整理：r/ClaudeAI 的 agent 安全性爭議、r/ChatGPT 的 GPT 5.5 guardrail 爭議、r/LocalLLaMA 的本機 LLM 現況，以及 Anthropic 宣布 Claude for Creative Work。
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1M context isn't about holding more — it's about managing better
Claude Code's context window grew from 200k to 1M. The instinct is to put more in. That instinct is wrong. Five session management operations, four strategy rules, and the two most common ways to break your own context.
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Knowledge base deep clean: using AI to find months-old problems
Rules trimmed from 13,020 to 7,590 tokens. 92 broken wikilinks. Five root causes behind a failing todo system. Four days of cleanup, one quarterly SOP.
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1M Context 不是裝更多，而是管理更好：Claude Code Session Management 心法
Claude Code 的 context window 從 200k 長到 1M，但更大不代表更好用。這篇整理五種 session 管理操作（Continue / rewind / clear / compact / Subagents）、四大策略、以及最容易踩的兩個坑。
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Claude Code this week: 1M context as a management problem, quota anxiety goes collective, SpaceX takes Cursor
Observations from 4/23–4/29: the right mental model for 1M context, Claude quota anxiety as a subscription design phenomenon, SpaceX beating Microsoft to Cursor for $60B, Claude 4.7 identifying a journalist from 125 words, and what happens when you let Claude Code DJ.
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See the Outside, Think the Inside: Two Claude Skills That Pair
I saw a competitor selling well and my first reaction was anxiety. But before letting anxiety win, I wanted to actually understand what it was. Lately I have been pairing two Claude Skills for this — H/V analysis to see the outside, first-principles to see the inside.
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Claude Code 這週整理：1M Context 怎麼用、額度焦慮集體發作、Cursor 被 SpaceX 搶走
4/23–4/29 這週的觀察與整理：1M context window 的正確心態、Claude 額度焦慮進化成集體現象、SpaceX 搶在微軟前面拿下 Cursor、Claude 4.7 根據 125 字認出記者、live coding 做音樂的副作用。
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看清外面、想清裡面：兩個 Claude Skill 的分工
偶然看到一個競品賣得很好，第一反應是焦慮。但焦慮之前，我想先搞清楚它到底是什麼。最近用兩個 Claude Skill 把這件事做透——橫縱分析法看外面，第一性原理看裡面。
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知識庫大掃除：用 AI 幫你找到埋了幾個月的爛帳
Rules 從 13,020 降到 7,590 tokens、92 個 wikilink 斷連、待辦系統五大根因——記錄一次花了四天的知識庫健檢，以及整理出來的季度 SOP。
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A Legal Counsel Used Claude Code to Catch Patent Infringement — Days Down to Hours
A legal counsel at a mid-sized company took our Claude Code course, then compressed a multi-day patent infringement audit into a single day — and actually caught a real case that is now in legal proceedings. This story finally turns "Claude Code is not just for engineers" from a slogan into a fact.
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法務用 Claude Code 抓專利侵權，從幾天變成一天
一位幾十人公司的法務上完 Claude Code 課之後，把原本要好幾天的專利侵權查核壓到一天，而且真的抓到送上法律程序。這篇想記下這個案例，因為它讓「Claude Code 不是只給工程師用」這句話從口號變成事實。
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My Claude Code Automation Stack: /loop, Monitor Tool, the Skill System, Obsidian Reflection Reviews
From /loop clocking in for me at ERP, to Monitor Tool as a background event gatekeeper, to Google Map MCP saving browser clicks, to Obsidian + Mirror framework for weekly reflection. Here's my six-month Claude Code automation stack, plus a clarification of how commands and skills actually split.
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我家的 Claude Code 自動化工作流：/loop、Monitor Tool、skill 體系、Obsidian 反思週報
從 /loop 指令幫我打 ERP 卡、Monitor Tool 做背景事件守門員、Google Map MCP 省瀏覽器操作、到 Obsidian 搭 Mirror 框架做反思週報——整理這半年我家 Claude Code 的自動化架構，順便釐清 commands 跟 skills 到底怎麼分。
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Six Months with Claude Code: From First Affection to Hesitation, From Overtime to Detox, From Mandarin Circles to the Thai Community
From January to April, my state of mind with Claude Code went from "that PTT-generation affection for the CLI" to "20x hesitation" to "AI detox" to "practicing Thai at a Bangkok meetup." Here's the six-month arc, along with the nights agents worked overtime for me until 5 AM.
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Claude Code 用了半年：從好感到猶豫、從加班到 detox、從中文圈到泰國社群
從 1 月到 4 月陪著 Claude Code 一起長大半年，我的心態從「PTT 世代對 CLI 的莫名好感」變成「20x 的猶豫」變成「AI detox」變成「泰國社群練泰語」。整理一下這半年的軌跡，連同那些對自己講越來越 nerdy、agent 幫我加班到凌晨五點的日子。
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Two Months of Claude Code Harness Ops: Crashes, Zombies, Cache Misses, and Plan Mode Edges
From March to April, running Claude Code as a long-running harness surfaced a bunch of issues. Survival tactics during the outage, my hook for cleaning up zombie processes, the silent memory bloat fixed in 2.1.86, the resume cache-miss fix in 2.1.90, and the Plan-Mode-question-density problem after 4.7.
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Claude Code Harness 兩個月運維史：當機、殭屍、快取、Plan Mode 的邊邊角角
從 3 月到 4 月，Claude Code 作為長時間運轉的 harness，踩過的幾個點：當機時的求生策略、我自己寫的 hook 清殭屍進程、2.1.86 的記憶體暴增修復、2.1.90 修好的 resume cache miss、還有 Plan Mode 問題太多的 4.7 癥結。
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Claude Code This Week: Offloading CLAUDE.md, Quota-Saving Tricks, Ghostty Click Fix
A handful of Claude Code settings and money-saving tricks I picked up this week — how Rules/Memory/Hooks offload CLAUDE.md, fixing cmd+click in Ghostty No Flicker mode, dispatching long-read work to Haiku for quota relief, and the cache difference between pasting images and editing prior messages after 4.7.
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Claude Code 這週整理：分擔 CLAUDE.md 的進階設定、省 quota 技巧、Ghostty 點擊設定
本週 Claude Code 累積的幾個實用設定與省錢技巧——Rules/Memory/Hooks 如何分擔 CLAUDE.md、Ghostty No Flicker 模式下連結點擊的修法、長文本用 Haiku 分派省 quota、4.7 後貼圖片跟改訊息對快取的差別。
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Opus 4.7 After One Week: From the System Card to the Roasting, Where Did It Go Wrong?
Opus 4.7 launched on 4/16 and the Chinese and English communities ended up with opposite takes. The system card reads like a full win, but real usage burns quota at roughly 2x what Anthropic claimed, and Reddit spent the week roasting it. Here's what I saw, and why I rolled back to 4.6.
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Opus 4.7 上線一週：從系統卡到火烤文，到底哪邊出了問題
Opus 4.7 上線一週，系統卡數據看起來全面超越 4.6，但實測下來燒 quota 是官方宣稱的 2 倍，Reddit 一片火烤文。整理這週的災情、逆向分析、以及我自己退回 4.6 的路徑。
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90% of People Are Two Years Behind: The Real AI Adoption Gap
I demonstrated Claude Code to friends and they were all amazed. Then I gave them free Pro trial passes — three of them. Not a single one was used. That told me a lot about how AI adoption actually works.
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Claude Code Subscription Guide: The Real Gap Between Pro and Max
How much does Pro actually give you? Is Max worth it? Why does Cowork burn through tokens so fast? What does "2x usage" actually mean? These questions come up constantly — here's everything I've figured out over the past few months.
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Why Claude Code Only Reaches Its Full Potential in the Terminal
The terminal isn't just another way to open Claude. It's the environment where Claude actually gets to operate without constraints. Multi-window workflows, speed, resources, Ghostty — a full confession from a CLI believer.
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90% 的人落後兩年：AI 採用的真實落差
我把 Claude Code 示範給朋友看，他們都說驚艷。然後我把免費的 Pro 體驗 pass 發給他們——三張，一張都沒被用過。這件事讓我想清楚了很多關於 AI 採用的事。
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Claude Code 訂閱怎麼選：從 Pro 到 Max 的真實落差
Pro 的額度到底有多少？Max 值不值？Cowork 為什麼很燒 token？週額度的「雙倍」到底是哪個雙倍？這些問題我都被問過不只一次，用這篇把幾個月來的觀察整理清楚。
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為什麼 Claude Code 在終端機裡才是完全體
終端機不只是另一種打開 Claude 的方式。它是讓 Claude 真正解放的環境。多視窗、速度、資源、Ghostty——這是一個 CLI 信徒的完整自白。
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What Anthropic Did This Time: Cache Reduction and Token Anxiety Injection
Starting in early April, some Max and higher accounts had their subagent cache duration quietly reduced from 1 hour to 5 minutes — no announcement. Around the same time, users found a hardcoded "token remaining" warning being injected into Claude's context, causing it to cut work short prematurely. How to check your own setup, and what this pattern means.
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Claude Desktop vs CLI: Why I Still Use the Terminal After the Redesign
Claude released a redesigned desktop application — better looking, friendlier for newcomers. But if you ask me which one to use, the answer is still CLI. Not nostalgia, just feature gap and resource efficiency.
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hermes-CCC: Bringing All 46 Hermes Agent Capabilities into Claude Code
Someone ported the entire NousResearch Hermes Agent into 46 native Claude Code Skills. No OAuth, no external processes, just restart CC and you're ready. The core philosophy is "procedures-as-prompt" — structured markdown instruction scripts drive AI behavior without writing a single line of code.
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Anthropic 這次幹了什麼：快取縮水與 Token 焦慮注射
4 月初起，部分 Max 以上帳號的 subagent 快取維持時間被偷偷從 1 小時改成 5 分鐘，零公告。同期有用戶發現 Claude 被注入固定的「剩餘 token 警告」，導致 Claude 提前縮短工作。怎麼自查，以及這件事代表什麼。
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Claude Desktop vs CLI 差在哪——改版之後我為什麼還是用終端機
Claude 推出了改版的桌面應用程式，設計更漂亮、對新手更友善。但如果你問我要用哪個，答案還是 CLI。不是情懷，是功能差距和資源效率的問題。
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hermes-CCC：把 Hermes Agent 的 46 個能力全部裝進 Claude Code
有人把 NousResearch 的 Hermes Agent 整套行為拆解成 46 個 Claude Code 原生 Skill。沒有 OAuth、沒有外部進程、重啟 CC 就能用。核心設計哲學是「procedures-as-prompt」：用結構化 markdown 指令稿驅動 AI 行為，不用寫一行程式碼。
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This Week in the Claude Code Ecosystem: Four Resources I Bookmarked
Enterprise office tools, Taiwan local services, a hobby vertical, beginner onboarding—four different corners of the Claude Code ecosystem all shipped something this week. Each represents a use case that's still underexplored.
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本週 Claude Code 生態觀察：四個我收藏的新資源
企業辦公工具、台灣本地服務、興趣領域、初學者入門——這四個角落本週都冒出了新的 Claude Code 資源。每一個都代表一類還沒被充分開發的使用場景。
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Digging into Claude Code's JSONL: Manual Context Usage, Cache Types, and Compact Detection
Claude Code's `/stats` only tells you the total token count, but the JSONL files hide a lot more—cache types, compact triggers, image-triggered cache misses. Here are the useful formulas I collected while building cc-audit.
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挖 Claude Code 的 JSONL：手動算 context 用量、分辨快取類型、偵測 compact
Claude Code 的 `/stats` 只告訴你總 token 數，但 JSONL 檔案裡其實藏著更細的資訊——快取類型、compact 觸發、貼圖 cache miss 都能手動算。這是我最近做 cc-audit skill 時整理出來的幾個實用公式。
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cc-audit: A Skill That Forces You to Save Claude Code Quota
I turned my viral list of quota-saving tips into a skill. Hand the GitHub link to Claude Code to install, and it'll audit your settings, recent sessions, rules bloat, and context usage, then hand back an actionable fix list.
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cc-audit：一個強迫你省 Claude Code 額度的 Skill
把我之前整理的一千多讚的省額度技巧全部做成 skill。丟給 Claude Code 安裝後，它會逐條檢查你的設定、近期 session、rules 膨脹、context 用量，給出可執行的修正清單。
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Make a Claude Code Tutorial Video in 30 Minutes with Remotion Skill
I'd had the Remotion skill installed for a while, mostly just playing with it. Once I started making a free Claude Code tutorial series, I realized how good it actually is—from script discussion to export, 30 minutes gets you a 15-minute video with no retakes.
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用 Remotion Skill 半小時拍一支 Claude Code 教學影片
Remotion skill 我下載好一陣子了，一開始只是玩玩。最近開始錄 Claude Code 免費教學系列才發現真的太好用——從口白討論到剪輯渲染，半小時出一支 15 分鐘影片，不 NG 也不費力。
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Is Claude Getting Dumber? Someone Finally Brought Data
People have been complaining Claude is getting dumber for weeks. Anthropic's response has been "it's a usage problem." Then someone pulled the JSONL and showed it's measurable, not vibes. The Issue got closed anyway.
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Claude 變笨了？這次有人拿出數據證據
大家抱怨 Claude 變笨已經好幾個禮拜了，Anthropic 的回應一貫是「使用習慣問題」。終於有人從 JSONL 扒出數據，證明不是體感而是實測——但 Issue 還是被秒關。
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Claude Code's Cache Crisis: Why Your Quota Burns So Fast
A Reddit user reverse-engineered two official bugs, and combined with the compounding effect of 1M-token context, your quota might be silently burning at 20x the expected rate.
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How Claude Code Skills Actually Load: Lazy Loading and a 30-50% Trigger Rate
Skills don't dump all their prompts into context by default. They load layer by layer on demand. But passive trigger rate is only 30-50%, so slash commands are your safest bet.
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Claude Code 的快取危機：為什麼你的額度燒得那麼快？
Reddit 大神逆向工程挖出兩個官方 Bug，再加上百萬 token 上下文的複合效應，你的額度可能在背後被吃掉 20 倍。完整事件始末與修復紀錄。
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Claude Code Skills 機制解密：按需載入與觸發率真相
Skills 不會把全部提示詞預設注入上下文。它是一層一層按需載入的。但被動觸發率只有 30-50%，打 slash 才是最保險的。
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Claude Code Source Leak: Three Secrets Unearthed by Reddit
Someone reverse-engineered Claude Code and found a hidden virtual pet system, next-gen model deception rate data, and an "Undercover Mode" that strips AI attribution from Anthropic employees' commits.
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Claude Code 源碼洩漏：Reddit 大神挖出的三個秘密
有人對 Claude Code 做了逆向工程，挖出了隱藏的電子寵物系統、下一代模型的欺騙率數據、以及讓 Anthropic 員工隱藏 AI 身份的 Undercover Mode。
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Anthropic's Trust Crisis and My Backup Plan
They quietly slashed quotas, went silent for a week, and only responded when they got caught. When your work is deeply tied to a service that can't even hit two nines of uptime, a backup plan isn't optional—it's essential.
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Anthropic 信任危機與我的備援方案
偷改額度、裝死一週、被發現才滅火。當你的工作已經深度綁定一個不到兩個 9 uptime 的服務，備援方案不是選項，是必要。