duopingtai

duopingtai is a skill for Claude Code, Codex from hanzhcn/laohan-skills. It costs 99 tokens per session (907 once invoked), scanned A, original, MIT.

A rewriting workflow that adapts one script or article into versions for Douyin, Xiaohongshu, and WeChat Official Accounts. It changes the format and tone for each platform while keeping the core information consistent.

In plain words
What is it for?
Use it to create a short-video script, a Xiaohongshu text post, and a longer WeChat article from supplied source material.
Why use it?
It removes the need to rewrite the same source separately for different publishing formats. It also provides platform-specific structure, length, and formatting rules.

Skill for Claude CodeCodex

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

Good fit Use it to create a short-video script, a Xiaohongshu text post, and a longer WeChat article from supplied source material.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hanzhcn/laohan-skills/laohan-duopingtai
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 hanzhcn/laohan-skills --skill laohan-duopingtai
Clone the repo
git clone --depth 1 https://github.com/hanzhcn/laohan-skills

Made for: Claude Code, Codex.

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 duopingtai

README.md
[![agentmods](https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-duopingtai/github.svg)](https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-duopingtai)
Your own site
<a href="https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-duopingtai"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-duopingtai/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 duopingtai

Your own site · 80×15
<a href="https://agentmods.dev/skills/hanzhcn/laohan-skills/laohan-duopingtai"><img src="https://agentmods.dev/badge/skills/hanzhcn/laohan-skills/laohan-duopingtai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 907 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.
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 $0.00099 $0.00907
Opus 5.5 $0.00040 $0.00363
Sonnet 5.5 $0.00020 $0.00181
Haiku 4.5 $0.00010 $0.00091

Measured 16d ago against content hash 6782eeb52728, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

duopingtai 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 16d 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.

laohan-duopingtai/SKILL.md · 76 lines

What it actually says

多平台改写 Skill

边界(2026-09-20治理P2-20):本工具不进入episode生产合同。episode内的四平台发布文案固定由②按schema 1合同生成(抖音/视频号/小红书带#老韩AI、B站带老韩AI,四平台≠本工具的三平台),勿用本工具产出发布文案。自由改写场景不受此限。

将一段口播稿或文章,改写为适合抖音、小红书、公众号三个平台的版本。

输入要求

用户需提供一段口播稿或文章原文。如果用户没有提供,主动要求用户提供原文。

改写规则

抖音版

  • 格式:短视频口播稿,保持口语化
  • 字数:必须达到原文的 60%-80%。具体操作:保留原文所有核心段落,只删过渡句和重复表达,不删观点、数据、步骤
  • 开头:必须用痛点/反常/好奇心钩子开头,禁止"大家好"式开场
  • 结尾:一句话收束 + 一个可操作步骤
  • 禁止:书面语、长句、排比句、空洞感叹
  • 自检:写完后统计字数,如果低于原文60%,说明删多了,补回被删的核心内容

小红书版

  • 格式:图文笔记(不含图片,只出文字内容)
  • 标题:单独一行,15字以内,用「」包裹
  • 正文:每段 1-2 句话,段落间空行
  • emoji:每个要点前加 1 个相关 emoji,全文不超过 8 个
  • 标签:末尾加 3-5 个 #标签
  • 禁止:长段落、纯口号、过度堆砌 emoji

公众号版

  • 格式:深度长文,带小标题结构
  • 字数:必须达到原文的 120%-150%。具体操作:每个核心观点都要展开论述,增加具体场景描述、使用体验、数据解读,不能只罗列要点
  • 标题:单独一行,20字以内,有信息量(不要标题党)
  • 结构:开头引出问题 → 2-3 个核心观点(带小标题)→ 结尾总结 + 互动引导
  • 禁止:口语化表达、emoji、短视频节奏
  • 自检:写完后统计字数,如果低于原文120%,说明展开不够,回到每个小标题下补充具体论述

输出格式

用以下格式输出,三个版本之间用分隔线:

## 抖音版
[改写后的口播稿]

---

## 小红书版
「[标题]」

[改写后的图文笔记正文]

#标签1 #标签2 #标签3

---

## 公众号版
[标题]

[改写后的长文]

注意事项

  • 核心信息(观点、数据、结论)三个版本必须一致,只是表达方式不同
  • 不要在任何一个版本中凭空增加原文没有的信息
  • 如果原文太短(少于100字),主动提醒用户"原文较短,公众号版可能展开不够充分"
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. 16d ago First seen · 76 lines · 99 tokens per session scan A 6782eeb52728

Subscribe to this mod's changes

duopingtai is a skill published in the GitHub repository hanzhcn/laohan-skills (13 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 907 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-01.

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