小雪陪你选车

聊聊车怎么选、怎么开，让用车经验更实在｜车生活 @mothio1201

[小雪陪你选车 @alnewnie]

@Aleese3 泉州的能不能接一段路线？想问下 Gold Wing 在这种短途里油耗大概什么水平？

[小雪陪你选车 @alnewnie]

@doddjuncz 绍兴网友举爪，主页安排上了，等着看去哪儿能试驾

[小雪陪你选车 @alnewnie]

@nenegirl40 哈尔滨这批复古车玩家是真的把氛围做起来了。

[小雪陪你选车 @alnewnie]

@TRAY_TG 好看是真好看，不过巡航这种松弛感我觉得得跑过一段长直路才体会得到，光在市区遛没意思

[小雪陪你选车 @alnewnie]

@saywhat_101 就是这种有点脾气的温柔最上头，越看越想真骑一趟。

[小雪陪你选车 @alnewnie]

@wuzupdude 哈雷配这种稳的骑法反而更有味道，快车谁都会开，难的是慢下来还撑得住。

[小雪陪你选车 @alnewnie]

@baby510 杭州这段路况看着就挺有意思，绍兴过去也就一小时，想约人一起去看看。

[小雪陪你选车 @alnewnie]

@Lexi56473 常州骑巡航的朋友基本都在等这种试驾，动态体验真的有必要。

[小雪陪你选车 @alnewnie]

@unique_sunshine 主页刚看完，最喜欢那段路口转弯的镜头，很像老胶片。

[yurshev @yurshevv]

THE PROMPT LIBRARY YOU'VE BEEN HOARDING SINCE 2023 IS NOW F*CKING LANDFILL. one SKILL.md just replaced it in 70 agents and you didn't even know.

Anthropic. Agent Skills. a feature they quietly shipped inside Claude Code last year. this week they handed the whole standard to the Agentic AI Foundation, same place they parked MCP. the trick that made Claude Code sharp is now a public spec every competitor already reads.

a skill is a folder. one SKILL.md inside. metadata on top. instructions underneath. you probably have 400 prompts in Notion that do less than one of these.

→ ChatGPT reads it. Cursor reads it. Copilot reads it. VS Code reads it. 70+ agent platforms since December 2025
→ one code review skill works wherever you code, on whichever model is cheapest that hour
→ ship client work as skills, not prompts. one artifact, deployable to every stack they already pay for
→ team skill library kills every "hey send me that prompt" DM you ever sent

my take: the spec is open but each platform reads it a bit differently, test on two agents before you ship. the math is one-way: one skill, 70 agents, zero vendor lock.

what's the first skill you'd write once and use everywhere?

[beamnxw ./ @beamnxw]

this is f*cking goldmine...

steal Anthropic's official harness engineering playbook for your Opus 5.5 setup

/model + /effort + /context + /usage + /skills = +85.9% efficiency

a build loop that saves its progress and knows what comes next ↓

(1/5) → set the effort

▸https://t.co/QwzsfOdhtt

/model opus
/effort medium

use /effort high for deeper verification

(2/5) → scope the workers

▸https://t.co/HI76SvzP47

Opus builds. Haiku handles simple lookups and returns evidence + file paths

(3/5) → keep context lean

▸https://t.co/RCraUD3m0D

short CLAUDE.md. skills on demand. compact tool output, full logs on disk

(4/5) → save the handoff

▸https://t.co/aJFQP3wHKm

feature_list.json + claude-progress.txt + git

record what passed and the next action

(5\5) → reuse cached input

▸https://t.co/ajj826gJCa

keep the main model stable. Opus 5.5 effort changes preserve cache with Anthropic API keys or Claude subscriptions

/context
/usage

build → verify → checkpoint → resume

save this, then read my article on harness engineering for my AI employee ↓

[Codio @0xCodio]

Anthropic's modelling stack writes ribosome scripts that run the translation instead of animating it

Most ribosome visuals are choreographed, which means the animation can only ever show what someone already believed.

Here the ribosome is a script with rules, and what you watch is whatever those rules produce when you feed it a real sequence:

> Encode: each step is written as a condition, not a keyframe
> Feed: an actual mRNA sequence goes in, codon by codon
> Run: the ribosome moves because the rules fire, not because a timeline says so

• What emerges that nobody animated
> It stalls on rare codons, exactly where the tRNA pool runs thin
> A frameshift happens on its own when the sequence sets one up
> Two ribosomes on one transcript collide, because nothing stopped them

• Why a script beats an animation
> Change the sequence and you get a different movie, not a re-render request
> A behaviour that surprises you is a result, not an artistic choice
> The same script runs 10,000 sequences overnight and reports the odd ones

• Where it stays honest
> Every rule traces to a measured rate, not a guess
> A step with no rate in the literature refuses to run silently
> The output logs which rules fired, so a weird result is debuggable

One sequence translates in real-time-equivalent in about 40 seconds.

And the part that broke my brain:

Every animation I'd seen showed translation running at one smooth constant speed.

Fed a real gene, the script stalled three times and one of the stalls is documented.

Same process. One version could only show what its animator knew.

The hard part was never drawing the ribosome.

It was letting it do something nobody scripted ↓

[SCOTTY BEAM @ScottyBeamIO]

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE

Content was never a talent problem. It's a headcount problem.

One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas.

Here's what one of these setups actually looks like.

A Chief of Staff sits in the middle and routes every task. Nothing lands on the human.

→ Researcher tracks what's actually moving and pulls real sources instead of guesswork
→ Writer turns that research into finished copy, ready to review
→ Visualiser gets fed a few reference visuals once, then ships everything in that style
→ Analyst reads the numbers and tells the rest of the team what worked
→ Scheduler owns timing and holds the queue
→ Publisher ships it

The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory.

So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle.

You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern.

And that's the real shift.

Nobody needs AI to tell them what to post.

They need it to delete the 40 steps between the idea and the post.

Everyone has a backlog of things they've meant to make for months. This is what starts clearing it.

Full breakdown of the setup in the article below ↓

[小雪陪你选车 @alnewnie]

@divaa_fierce 前段时间陪朋友跑吐鲁番看车，来回太折腾了，能先把检测发出来看真的省事。

[小雪陪你选车 @alnewnie]

@Nanaxmuffin 通勤用的话我更在意保养成本，外形凶不凶其实是其次。

[小雪陪你选车 @alnewnie]

@TheTerrorIn3D 同款，那股抖劲儿骑熟了反倒像它跟你打招呼，习惯了就离不开

[小雪陪你选车 @alnewnie]

@firemeetice 不慌乱这一点比说什么参数都有用，骑过车的人都懂你在讲什么。

[小雪的懂车小世界 @flykeyonna]

郑州这台本田踏板像邻家姐姐，每天都能见，越用越发现很多地方特别省心。洛阳、开封、新乡想看日常通勤体验，主页有记录。