wjs-polishing-x-engagement

wjs-polishing-x-engagement is a skill for Claude Code, Codex from jianshuo/claude-skills. It costs 175 tokens per session (2,058 once invoked), scanned A, original, MIT.

A Chinese-language writing helper that rewrites a plain social-media post into two or three short versions with a factual basis and an invitation for replies.

In plain words
What is it for?
Use it to polish Chinese posts for platforms such as Twitter, Weibo, or similar services by adding a checked fact and different interaction hooks.
Why use it?
It makes an ordinary post easier to trust and easier for readers to respond to, while keeping the wording brief and conversational.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to polish Chinese posts for platforms such as Twitter, Weibo, or similar services by adding a checked fact and different interaction hooks.

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Install with agentmods
npx agentmods add skills/jianshuo/claude-skills/wjs-polishing-x-engagement
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add jianshuo/claude-skills --skill wjs-polishing-x-engagement
Clone the repo
git clone --depth 1 https://github.com/jianshuo/claude-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin wjs-polishing-x-engagement/plugin install wjs-polishing-x-engagement after adding the marketplace above.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for wjs-polishing-x-engagement

README.md
[![agentmods](https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-polishing-x-engagement/github.svg)](https://agentmods.dev/skills/jianshuo/claude-skills/wjs-polishing-x-engagement)
Your own site
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-polishing-x-engagement"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-polishing-x-engagement/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for wjs-polishing-x-engagement

Your own site · 80×15
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-polishing-x-engagement"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-polishing-x-engagement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 175 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,058 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00175 $0.02058
Opus 5 $0.00088 $0.01029
Sonnet 5 $0.00035 $0.00412
Haiku 4.5 $0.00017 $0.00206

Measured 12d ago against content hash f3f08c73d449, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

wjs-polishing-x-engagement scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

wjs-polishing-x-engagement/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Tweet Engagement Polish(中文推文互动化改写)

把一句平淡的话,变成读者忍不住接话的一条推文。两件事叠在一起就行:一个真事实(可信、有料)+ 一个钩子(留个缺口让人补)。

风格铁律:短、白、日常 ⚠️ 最重要

这是最容易翻车的地方,优先级最高:

  • 越短越好。 一条推文最好一两句读完,能删的字一律删。长 = 劝退。
  • 说人话。 日常口语,像微信里跟朋友讲话。不用书面腔、文艺腔,不堆形容词。
  • 不煽情、不上价值、不排比。 别"走心""恍如隔世""那一下的心跳"这种文青腔。平淡日常的事就平淡地说。
  • 钩子直给。 想问就直接问,别绕弯子铺垫。

正反对照(同一条虹桥怀旧帖):

  • ❌ 太文青:「变的是机场,没变的是走出航站楼那一下的心跳。」
  • ✅ 短而白:「那会儿这还是上海唯一的机场,浦东 1999 年才开。你第一次坐飞机去哪儿?」

工作流程

第 1 步:抓核心

原文到底想说什么?找出那个可以被一个真事实坐实的点(一个观点、一种感受、一个人/事/地)。

第 2 步:联网查一个真事实 ⚠️ 必做

整条推文的可信度全靠这个事实是真的。

  • web_search 查一个具体到能核实的事实:确切年份/数字/人名/地名、"第一/最后/唯一"、纪录、反常识的真相。
  • 优先挑反常识或大家"似懂非懂"的——最容易勾起"我知道!"或"真的假的?"。
  • 绝不编造、不夸大、不张冠李戴。 查不到就换角度,或直说"没查到可靠事实"。宁可换角度,也别拿假事实当钩子——那是造谣、毁号。
  • 数字、年份、人名落笔前再核一遍。

第 3 步:套不同钩子,写 2-3 个版本

同一个真事实,写 2-3 个钩子不同的版本(换的是参与方式,不是换语气)。每版都遵守上面的风格铁律。钩子类型:

  • 历史规律外推钩(最强):用 2 个以上真事实摆出一条暗规律,外推到当下,结论留空让人猜。例:"存储便宜,出了 Gmail;带宽便宜,出了 YouTube。智能便宜,会出什么?"
  • 提问钩:抛一个人人都有答案、零成本就能甩一句的问题。例:"你第一次坐飞机去哪儿?"
  • 填空钩:挖空一个"答案就在嘴边"的词/数字让人补(挖空的必须是真正确的)。例:"贝多芬写《第九》时已经完全 ___ 了。"
  • 反常识钩:先甩一个反直觉的真相,引人反驳或验证。例:"以为 X,其实是 Y。"
  • 二选一/站队钩:给两个选项让人选边,比开放回答门槛更低。例:"A 还是 B?报个数。"

不要每版都用同一种钩子;别牺牲原意(是给原话加可信度和钩子,不是换话题)。

输出格式

【版本 1 · 提问钩】
<推文正文>
↳ 钩子:一句话说明为什么勾人

【版本 2 · 填空钩】
<推文正文>
↳ 钩子:……

末尾附一行事实来源,方便用户核实。

第 4 步:配图提示(有就提,没有就跳过)

带图传播力更强,史实型推文往往正好有经典照片/对照图。产出后判断有没有现成的、画面感强的图(老照片、前后对照、数据图);有就用 image_search 找出来给用户,并提醒优先用公共领域来源(国会图书馆、国家档案馆、Wikimedia)、附上出处。没有合适的就别硬凑。

标杆示例

一条真实爆款,也是本 skill 的风格范本(短、白、有事实、有缺口):

存储便宜,出了 Gmail;带宽便宜,出了 YouTube。智能便宜,会出什么?

为什么爆:两个真事实(Gmail 2004 年 1GB、约 100 倍于竞品;YouTube 2005 年)摆出"成本暴跌→催生时代级产品"的规律,再把结论留空,读者忍不住接话、还能借预测显见识。全程没有一句多余的形容词。

改写示例

原文(观点型): AI 越来越便宜了,以后肯定会冒出很厉害的新产品。

【版本 1 · 历史规律外推钩】
存储便宜,出了 Gmail;带宽便宜,出了 YouTube。
智能便宜,会出什么?
↳ 钩子:真事实摆规律 + 结论留空,接话门槛极低。

【版本 2 · 反常识钩】
Gmail、YouTube 不是靠想法赢的,是踩中了成本暴跌。
这轮暴跌的是"智能",下一个 Gmail 你押谁?
↳ 钩子:打破"靠创意取胜"的直觉 + 站队式开放问题。

事实来源:Gmail 2004/4/1 上线、1GB 免费存储(约竞品 100 倍);YouTube 2005 年创立、当年 12 月上线。(发前用 web_search 复核)

原文(日常型): 忽然感觉刚出虹桥机场,如同 30 年前第一次坐飞机来虹桥。

Read the full file on GitHub · 121 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 121 lines · 175 tokens per session scan A f3f08c73d449

Subscribe to this mod's changes

wjs-polishing-x-engagement is a skill published in the GitHub repository jianshuo/claude-skills (129 stars, last pushed 23d ago), licensed MIT. It adds 175 tokens to every session and 2,058 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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