跟读练习: Claude Code Is Wasting Tokens... Microsoft Built a Fix - 通过视频学习英语口语

选择练习模式

每种模式都会打开全屏练习室。

119 句

如果句子过短或过长，请点击 Edit 进行调整。

It seems there's a lot of heat with tools and extensions that claim to reduce token usage.

Many of these have been put to the test and they work well.

Now Microsoft just released their own, a free plugin that cut AI coding agent costs by 18 to 31 % in their tests.

And they didn't use a cheaper model or a different agent either.

It works with all the big names, so it's a win for us.

it's called token economizer

and it solves a problem you've probably seen yourself

you ask claude code to fix something fix this it tries a command gets an error

and then keeps running

and burning tokens up to find us a fix token economizer learns from those sessions it remembers how your repo works, removes tools you don't use,

and steps in when the agent keeps making the same mistake.

And the more you use it in the same project, the more tokens you actually save.

So let's install it and see what it actually does.

If you enjoy coding tools the speed of your workflow, be sure to subscribe.

We have videos coming out all the time.

Now I'm going to use

Cloud Code for this, but remember

Token Economizer also supports all the other big names.

First, I'll clone it and install the plugin right here.

We're going to run our git clone.

We're going to install the git plugin from the marketplace and make sure everything is ready to go.

That's installed all super straightforward.

Just keep the clone folder because the plugin runs from there.

Now I'll open one of my existing projects and we're going to fire up Claude Code.

Let's check the status.

All we need to do to check the status here is I'm going to run token economizer status.

This shows what the plugin has learned.

It shows what it's doing and the costs it has already tracked.

Now, quick note here, micro skills are turned off by default.

So I'm going to enable those and we'll circle back.

Then I'll refresh the tool catalog.

I'm going to run here a tool prune, refresh catalog.

Now I'll give Claude Code some tasks.

Let's start super simple.

I'm going to give Claude Code a task, build a unit test.

Very straightforward.

Run it.

Now notice I'm not changing how I use Claude code.

It's the same thing, just on Opus 5 .5, with all the prompts I would normally fire straight at it.

TokenEconomizer just works alongside it.

Now, in a repo where it's already watched several sessions, we can check what it's learned so far.

So here we are.

I'm going to run Microskills.

You can check.

You can run ToolPrune.

Here we can see any repo -specific info it's learned.

In tools, it's identified as unused.

If you install it for the first time, these might be empty.

It needs a few sessions to actually learn what the hell is going on.

And all of that info stays on your machine inside the token economizer folder.

There are really three parts to this.

Now, first up to the plate is called micro skills.

Say you're working on a project that needs a specific command to run its tests.

Claude code, it doesn't know that.

So it tries the usual command, gets an error, try something else and yeah, okay, it eventually gets it.

Great.

Except later when you start a new session, it might make the exact same mistake.

So there we are paying extra tokens, which I would rather not do.

Token Economizer looks at a previous session, all of them, and learns small details about the repo.

Things like which test commands actually work, which environment variables are needed, and where certain files live.

Once something has been confirmed enough times, it can give us that information to the agents at the start of a new session.

So instead of wasting tokens over and over again, the agent already has the answer.

Now next up to the plate is tool pruning.

When you start a coding agent, it can load a bunch of tools into its context, and those tool definitions use tokens,

even if the agent never touches them.

Token Economizer tracks which tools actually get used in your repo.

If a tool consistently goes unused, used, it can stop loading it in a feature session.

And if you need it again, you can just restore it.

Then finally, we go to something called a failure loop intervention.

You've probably watched an agent run a command, get an error, change one small thing and run almost the exact same command again.

Sometimes it just keeps repeating that process.

Token Economizer watches for these patterns.

When it thinks the agent might be stuck, it uses a judge model to check what's happening.

If it detects this loop, it sends the agent a short instruction to try a different approach.

And if the agent still can't recover, it tells you how to stop the turn.

It doesn't just freak out and stop, but does it actually save enough money to even matter?

That's sort of the question.

Yes, it appears to do pretty much that.

Microsoft in UC Berkeley tested

Token Economizer on...

277 SWE benched tasks across six repos using five different agent and model combinations.

And the average cost dropped between 18 .4 % and about 31%.

So the results were pretty good.

In four of the five combinations, tasks' success actually improved.

One saw a small decline, but across all 30 repository and agent model combinations, Token Economizer was cheaper than running without it.

And they even included the plugin's own model calls in those.

Token Economizer isn't completely free to run.

Some of its features use additional model calls.

So those reported savings already accounted for the overhead.

It is open source.

It works with the same agents we already use, and the info it learns stays local.

But I wouldn't expect all of us to see the same results.

Its first public release was in October of this year, and the biggest savings come from working in the same repositories over multiple sessions.

If you're constantly jumping between unrelated projects, there's much less to actually learn from it, or for it, I should say.

If your agent is doing something completely new, there might not be much repeated work to eliminate at all.

So ask yourself, based on the work you do, will this actually be useful?

If you use agents every day on one or a couple core projects, then yeah, this should help.

If you're working on the same repo over and over with Claude Code, Codex, yes, this is going to help.

But if you're building a ton of different projects or you're just playing around, this is not really going to change anything.

100

It's probably not even worth it.

101

So here's what I'd do.

102

Install Token Economizer on the repo you use the most.

103

Run it for a week, then check the status reports like I showed us and compare the costs of similar tasks.

104

If the agent is actually using fewer tokens and whether it's still completing your tasks properly, awesome.

105

It is working.

106

One thing to remember, each agent learns separately.

107

So whatever cloud code learns doesn't automatically carry over to Codex.

108

And don't judge it entirely on the first session.

109

That's why I say run it for a week.

110

The whole point is that it learns from repeated use.

111

If it's saving you money without getting in your way, keep it.

112

If not, you've got the answer.

113

So what it really does is takes a different approach to

114

reducing AI coding costs instead of making the model smaller or compressing your prompts.

115

It looks at the work your agent keeps wasting tokens on.

116

It remembers useful details about your repo, stops loading unused tools, and helps agents recover when it gets stuck.

117

I'm Josh from BetterStack.

118

If you enjoy coding tips and tricks like this, be sure to subscribe.

119

We'll see you in another video.

下载应用

流利口语所需的一切

AI 发音评分逐句打分

音标练习掌握每个音

词汇学习建立你的词库

词汇游戏边玩边学

扫码

Download on theApp Store Get it onGoogle Play

FOR YOU

本课的词汇与口语要点

这节口语课以视频“Claude Code Is Wasting Tokens... Microsoft Built a Fix”为素材。视频中反复出现的词有：token, agent, economizer, tool, repo。这段视频共有 119 个句子、1344 个单词可供跟读。讲话部分时长为 7:29。说话人语速较快，每分钟约 180 个词，会出现较多连读和弱读。 82% 的单词属于英语最常用的 3,000 词，其余的词建议在练习前先学一下。

视频中的重点词汇

视频中 15 个值得学习的单词，附发音和释义：

单词	发音	释义
token 名词	/ˈtoʊkən/	代幣 /代币, 籌碼 /筹码
install 动词	/ɪnˈstɔl/	安裝 /安装
clone 名词	/kloʊn/	克隆, 複製 /复制
cloud 名词	/ˈklaʊ̯d/	йүн, 雲 /云
skill 名词	/skɪl/	技巧, 技能
loop 名词	/luːp/	圈, 環 /环
recover 动词	/ɹɪˈkʌvɚ/	追回, 收复
subscribe 动词	/səbˈskɹaɪb/	簽署 /签署
catalogue 名词	/ˈkæt.əˌlɔɡ/	目錄 /目录
straightforward 形容词	/ˌstɹeɪtˈfɔː(ɹ)wə(ɹ)d/	簡單 /简单
folder 名词	/ˈfoʊldɚ/	卷宗, 文件夾 /文件夹
refresh 动词	/ɹɪˈfɹɛʃ/	提神
trick 名词	/ˈtɹɪk/	詭計 /诡计, 騙術 /骗术
alongside	/əˌlɔŋˈsaɪd/	旁邊 /旁边
compare 动词	/kəmˈpɛɚ/	比, 比較 /比较

视频中出现的短语动词

单词	发音	释义
come out 动词	/ˌkʌm ˈaʊt/	出, 出來 /出来
turn off 动词		關 /关, 關掉 /关掉

值得反复跟读的句子

视频中简短而完整的句子，可以直接用在日常对话里：

We're going to run our git clone.
Then I'll refresh the tool catalog.
That's why I say run it for a week.
If not, you've got the answer.
We'll see you in another video.

视频中的语法

说话人最常用的结构，并附上视频中的原话：

结构	视频中的用法
现在完成时 have/has + 过去分词 — 过去发生但与现在仍有关联的事	have been put · you've probably seen · has learned
被动语态 be + 过去分词 — 强调发生了什么，而不是谁做的	have been put · are turned · is called

需要注意的发音

说话人用了 35 次缩略和弱读形式，例如 I'm, you're, I'll。请按听到的简短形式来说。

“sh” 和 “zh” 音: combinations /kɑmbɪˈneɪʃənz/, refresh /ɹɪˈfɹɛʃ/, extension /ɪkˈstɛnʃən/, intervention /ɪntɚˈvɛnʃən/, instruction /ɪnˈstɹʌkʃən/
长单词——注意重音位置: combinations /kɑmbɪˈneɪʃənz/, intervention /ɪntɚˈvɛnʃən/, consistently /kənˈsɪstəntli/, eliminate /ɪˈlɪm.ɪ.neɪt/, repository /ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/

中文母语者容易读错的音：

/v/ — 不要读成 /w/，上齿轻触下唇: recover /ɹɪˈkʌvɚ/, solve /sɒlv/, intervention /ɪntɚˈvɛnʃən/, variable [ˈvæɹ.i.ə.bl̩], overhead /ˈəʊvəˌhɛd/
词尾辅音 — 要读清楚，后面不要加元音: combinations /kɑmbɪˈneɪʃənz/, unused /ʌnˈjuzd/, cloud /ˈklaʊ̯d/, loop /luːp/, subscribe /səbˈskɹaɪb/
/r/ 和 /l/ 的区别: variable [ˈvæɹ.i.ə.bl̩], separately /ˈsɛp.ɹət.li/

如何用这段视频练习

先完整听一遍视频，不要开口，记下不认识的单词。
先用 0.75 倍速逐句跟读，熟练之后再回到正常速度。
录下自己的声音并与原声对比，特别注意 token, install, clone 这类单词。

什么是跟读法？

跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。

影子跟读法: 阅读完整分步指南 →

跟读练习: Claude Code Is Wasting Tokens... Microsoft Built a Fix - 通过视频学习英语口语

选择练习模式

下载应用

推荐视频

9 Insane Claude Mods I Already Can't live Without

Why AI Tokens are so Expensive - Computerphile

Your AI Agent Starts Every Session Like a New Hire - Killian Carlsen-Phelan, Sonar

The easy way to keep your repos tidy.

Did Anthropic Kill Git?

So I tried Matt's skills...

Give Me 24 minutes, I'll Give You 1,000+ hours of Claude Knowledge

I Tested The Viral Reverse Engineering Repo

JUST $1 For Billions of Tokens?! (DeepSeek v4 Pro)

GitHub Copilot now controls your command line...

The 4-Hour Workweek in a World of AI

STOP Running Code On Your Computer