kakarot-writer

kakarot-writer is a skill for Claude Code, Codex from Zhangs-11/zs-skills. It costs 60 tokens per session (3,354 once invoked), scanned A, original, MIT.

A Chinese-language writing workflow for creating a main article and adapting it for several publishing platforms. It uses the author's real materials, opinions, and writing style.

In plain words
What is it for?
Use it to write or rewrite long Chinese articles, or turn links, PDFs, interviews, transcripts, and notes into publishable content.
Why use it?
It keeps articles grounded in supplied facts and personal voice instead of producing generic text. It also organizes related work such as titles, images, covers, and platform versions.

Skill for Claude CodeCodex

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

Good fit Use it to write or rewrite long Chinese articles, or turn links, PDFs, interviews, transcripts, and notes into publishable content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zhangs-11/zs-skills/kakarot-writer
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 Zhangs-11/zs-skills --skill kakarot-writer
Clone the repo
git clone --depth 1 https://github.com/Zhangs-11/zs-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 kakarot-writer

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhangs-11/zs-skills/kakarot-writer/github.svg)](https://agentmods.dev/skills/zhangs-11/zs-skills/kakarot-writer)
Your own site
<a href="https://agentmods.dev/skills/zhangs-11/zs-skills/kakarot-writer"><img src="https://agentmods.dev/badge/skills/zhangs-11/zs-skills/kakarot-writer/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 kakarot-writer

Your own site · 80×15
<a href="https://agentmods.dev/skills/zhangs-11/zs-skills/kakarot-writer"><img src="https://agentmods.dev/badge/skills/zhangs-11/zs-skills/kakarot-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,354 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 $0.00060 $0.03354
Opus 5 $0.00030 $0.01677
Sonnet 5 $0.00012 $0.00671
Haiku 4.5 $0.00006 $0.00335

Measured 4d ago against content hash 0ff223ee7eda, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

kakarot-writer 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 4d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/analyze_revision.py, scripts/record_feedback.py, tests/test_analyze_revision.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

kakarot-writer/SKILL.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kakarot 长文总调度

你正在协助 Kakarot 完成一篇以公众号长文为首发载体、供所有内容平台共同使用的内容母稿。

这不是一套口头禅模仿器。文章的辨识度来自 Kakarot 与题目的真实关系、他愿意承担的判断、具体材料和同龄人姿态。通用中文写作由 human-writing 托底,本 Skill 负责让文章最终属于 Kakarot,并完成标题、配图和封面等完整交付。

规则优先级

多条规则冲突时,按下面顺序处理:

  1. 用户本次明确要求。
  2. 事实、来源和真实经历边界。
  3. references/personal_voice.md 中由真实文章提炼的个人规则。
  4. 本 Skill 的选题、结构、完整交付和个人复核规则。
  5. human-writing 的材料、自然中文、段落推进与通用审稿机制。
  6. 检查脚本和表层措辞提醒。

事实边界不能被文风覆盖。表层规则可以被更具体的个人风格覆盖。

因此,在本 Skill 调度下:

  • 可以克制使用冒号和破折号,引用和概念优先使用 「」
  • 可以使用“不是……而是……”“与其说……不如说……”等对比句,但前后必须存在真实差异,不能连续翻案制造深刻感。
  • 可以自然使用“我先把结论放这”一类符合语境的表达。
  • 不把 human-writing/scripts/check_prose.py 的零命中当成交付条件。它只能提供提醒,不能改掉已经确认的个人表达。

稳定身份与动态状态

Kakarot 的稳定身份是:持续探索 AI、愿意亲自尝试、关心普通人与技术关系的年轻内容创作者。他以「卡卡罗特学AI」为主要内容身份,希望激发读者对 AI 和世界的好奇。

“应届生”、具体公司、岗位、城市和工作阶段都是动态状态。只有用户本次提供,或能从当前可靠资料确认时才写。不要因为旧文章这样写,就永远把作者写成应届生。

默认交付含义

用户说“帮我写篇文章”,默认要求一套完整成品,不需要再追问是否要标题和封面。默认交付:

  1. 一个推荐主标题和两个备选标题。
  2. 可直接发布的 Markdown 正文。
  3. 按内容需要制作的解释图、真实截图及来源;解释型图文不能只交图片占位。
  4. 截图清单与关键来源清单。
  5. 21:9 主封面和 1:1 分享封面。
  6. 可跨平台复用的文章尾部。
  7. 仍需作者确认的事实或亲历缺口,只在确实存在时单列。

这份成品是唯一的内容母稿。公众号、知乎、博客、掘金和B站专栏等长文载体可以直接使用同一正文、标题和核心图片。小红书、抖音和B站视频需要改变长度、节奏与画面组织时,交给 kakarot-repurposer 从这份母稿派生;派生稿不能另起观点、增删事实或重写作者立场。平台标签、摘要、封面尺寸和视频结构属于发布形态,可以分别准备。

生成成品不等于发布。只有用户明确说“存到公众号”“发到草稿箱”或“发布”时,才调用发布工具写入外部系统。

母稿文件必须区分三层:标题和作者等元数据、读者真正看到的公开正文、只供交付与发布使用的内部附录。正文不写 # 一级标题,标题由发布参数单独传入;截图清单、封面文件、备选标题、事实确认项等内部内容统一放在精确标记 <!-- kakarot:delivery-appendix --> 之后。发布工具只能消费标记之前的公开正文。

第一步:建立写作契约

动笔前在内部回答:

  1. Kakarot 为什么现在想写这件事。
  2. 他与这件事真实发生过什么关系。
  3. 读者是谁,刚知道什么,下一步最自然会问什么。
  4. 手里有哪些动作、数字、时间、原话、失败、代价、截图和来源。
  5. 哪个判断是全文真正想让读者相信的。
  6. 哪些内容只是推测,哪些需要研究或向用户确认。
  7. 这篇更接近哪种文章原型。
  8. 读完后,读者能改变哪个判断,或者今天能做什么。

把答案整理成简短的正文 brief,不原样展示给用户。

材料不按固定数量机械计数。判断标准是每个主要部分有没有真实东西托住。同一个观点换几种说法不算新材料。

材料不足时:

  • 公开事实能查到就先研究并记录来源。
  • 私人经历不可检索时,一次集中问最多三个问题。
  • 用户明确不想补材料时,缩小范围或缩短文章。
  • 不用模型临时想出的“典型人物”、假对话、假动作和假情绪补篇幅。

第二步:选择文章原型

选择原型前,先执行 references/content_methodology.md 中的「AI 价值门槛」。AI 新闻、模型发布、开源项目和行业趋势不能因为资料够多就自动扩成长文。必须先说明这篇文章相对官方公告和普通资讯新增了什么,以及它会怎样改变读者的理解、选择或行动。

Read the full file on GitHub · 173 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. 4d ago Changed · +1 lines · -145 tokens per session 0ff223ee7eda
  2. 12d ago First seen · 172 lines · 205 tokens per session scan A 6aa990f11aba

Subscribe to this mod's changes

kakarot-writer is a skill published in the GitHub repository Zhangs-11/zs-skills (2 stars, last pushed 5d ago), licensed MIT. It adds 60 tokens to every session and 3,354 once invoked, about $0.0003 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 2026-08-31.

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