Agent skill

Writing DNA Distiller

by larashero3-dotcom in larashero3-dotcom/writing-dna-skill

Distills a reusable Writing DNA from at least 20 complete articles by one author, account or brand, covering language, structure, topics, sources, thinking and visuals.

MITAuto-check: warningsWriting & Content

SKILL.md written in Chinese; this summary is our English description.

Install Writing DNA Distiller

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add larashero3-dotcom/writing-dna-skill --skill writing-dna-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install larashero3-dotcom/writing-dna-skill writing-dna-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
writing-dna-skill
GitHub stars
2.4k
Token cost
~1.8k tokens
SKILL.md length
400 words
Files
42 (incl. references, assets)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Distills a reusable Writing DNA from at least 20 complete articles by one author, account or brand, covering language, structure, topics, sources, thinking and visuals.

  • Works in 7 steps: :原始素材收集 → :元数据标注(_meta/ 目录) → :脚本分析(L1 表层语言) → …
  • Analyzing the writing style of an author or publication from past articles
  • SKILL.md covers 使用语言与模板, 一、目标, 二、蒸馏的六个层次 and 三、工作流程, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

The skill analyzes a corpus of an author's articles in six layers: surface language, article structure, topic logic, source strategy, cognitive framework and visual style, and merges the results into a `Writing-DNA.md` file. The aim is a set of operational rules rather than a summary, usable to understand an author's perspective, to imitate the style and to compare how different authors treat the same issue.

Work starts with collecting at least 20 articles as `.md` or `.txt` files, then annotating metadata for each, running script-based analysis of word frequency, sentence length and punctuation, and annotating structure by hand. Images are to be opened and read, because screenshots and tables often carry the evidence. Conversation language and output language are handled separately, with Chinese and English template sets and file names. When writing from the resulting DNA, the agent reads all distilled outputs and five related original articles.

When your agent uses it

  • Analyzing the writing style of an author or publication from past articles
  • Preparing a style guide so new posts match an existing brand voice
  • Comparing how two authors approach the same topic

Example prompts

  • “Distill the writing DNA of our company blog from these articles.”
  • “Analyze this columnist's structure and language habits and write Writing-DNA.md.”
  • “Write a post about remote work in the style captured in our Writing-DNA.md.”

Requirements

  • At least 20 complete articles saved as .md or .txt files

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. :原始素材收集
  2. :元数据标注(_meta/ 目录)
  3. :脚本分析(L1 表层语言)
  4. :结构标注(L2 文章结构)
  5. :选题与认知框架归纳(L3-L5)
  6. :视觉风格与排版分析(L6)
  7. :蒸馏产物整合

What it can do on your machine

Read from SKILL.md and the folder at commit ee3d97e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Writing DNA Distiller loads about 1.8k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 400 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningContains zero-width charactersSKILL.md:246
    这份文档应满足:⟨U+200B⟩**给任何一个没读过该账号/作者的人,他读完下笔能写出 70 分的近似风格文章——不仅文字像,视觉呈现也像。**

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from larashero3-dotcom/writing-dna-skill at commit ee3d97e, republished under its MIT licence (© larashero3-dotcom). 400 words, ~1,786 tokens.

Download SKILL.mdSave it as .claude/skills/writing-dna-skill/SKILL.md (or your agent's skills folder). This skill also uses 41 other files; get the full folder from GitHub.
name
writing-dna-skill
description
从至少 20 篇完整文章中蒸馏可复用的写作 DNA,分析语言、文章结构、选题逻辑、素材策略、认知框架和视觉风格,并生成 Writing-DNA.md;按该 DNA 写作时会读取全部蒸馏产物和 5 篇相关原文。用于中英文作者、账号、品牌或出版物的风格分析与一致性写作。 Distill reusable Writing DNA from at least 20 complete articles for Chinese or English authors, publications, brands, and accounts; use for language, structure, topic logic, source strategy, cognitive-frame, and visual-style analysis.

写作蒸馏器.skill

英文名:writing-dna-skill

使用语言与模板

将“对话语言”和“产物语言”分开处理:

  1. 使用用户的对话语言进行交互,除非用户明确指定其他语言。
  2. 用户明确指定产物语言时,以用户选择为准。
  3. 未指定时,使用原始语料的主要语言。
  4. 语料混合且无法判断时,使用对话语言。

中文产物使用 templates/author-corpus/zh/。英文产物使用 templates/author-corpus/en/,并按需读取 references/workflow.en.md 以获取英文文件名和表达规范。

分析产物中文文件名英文文件名
L1 语言 DNA语言DNA.mdlanguage-dna.md
L2 文章结构文章结构模板.mdstructure-patterns.md
L3-L5 认知框架写作视角与认知框架.mdcognitive-framework.md
L6 视觉风格视觉风格指南.mdvisual-style-guide.md
最终整合文档Writing-DNA.mdWriting-DNA.md

下文中出现产物文件名时,始终根据已选定的产物语言使用上表对应的文件名。

一、目标

从某个账号/作者的历史文章中,提炼出可复用的写作 DNA——不是摘要,而是可操作的规则集,用于:

  1. 理解 该账号/作者的写作视角、选题逻辑、语言风格
  2. 复刻 该账号/作者的写作风格(输出近似风格的文章)
  3. 对比 不同账号/作者在同一议题上的表达差异

二、蒸馏的六个层次

层次分析对象提取方法输出形式
L1 表层语言词频、句长、标点、修辞脚本统计词频表 + 句式清单
L2 文章结构开头 hook、正文架构、结尾收束人工标注结构模板(按类型分类)
L3 选题逻辑发布时机、切入角度、话题优先级归纳分类选题判断树
L4 素材策略引用来源类型、权威对象选取标准、数据使用方式阅读归纳素材偏好清单
L5 认知框架作者的世界观、价值判断、对主题的核心假设深度阅读核心命题列表
L6 视觉风格配图策略、排版格式、字体层级、色彩使用图文统计 + 截图采样视觉风格指南

原则:L1-L2 是"怎么写",L3-L5 是"怎么想",L6 是"怎么呈现"。完整的风格复刻需要三者结合。

跨层原则:图片内容必须纳入分析

许多文章的图片不是装饰——截图、对话记录、数据表格、用户评论中的文字是论证链的一部分。分析时必须打开图片查看内容,否则会遗漏:

  • L2 文章结构:截图在叙事中的承重角色(转折点在截图里、证据链由截图构成)
  • L4 素材策略:截图是核心素材形式,精确数据往往只存在于图片中
  • L6 视觉风格:图片的功能分类(证据型/演示型/数据型/叙事推进型/情绪型)和图文协作模式

执行要求:Step 3-6 的分析中,至少抽样 5-10 篇文章逐张查看图片内容,评估图片携带的实质性信息比例。


三、工作流程

Step 1:原始素材收集

目标:建立该账号/作者的文章语料库

  • 收集渠道:公众号、博客、Newsletter、官网、社交平台等历史文章
  • 数量建议:至少 20 篇完整文章
  • 文件格式:.md 或 .txt,存入对应目录的 raw/ 或 raw-corpus/ 文件夹
  • 覆盖范围:尽量包含不同时期、不同类型的文章(访谈 / 深度 / 短评)

文件命名规范:

YYYY-MM-DD 内容类型 文章标题-来源.md

Step 2:元数据标注(_meta/ 目录)

为每篇文章创建元数据记录,字段如下:

json
{
  "title": "文章标题",
  "date": "YYYY-MM-DD",
  "author": "作者姓名",
  "column": "内容系列名称",
  "article_type": "访谈 | 深度分析 | 短评 | 观察 | 综述",
  "topic_tags": ["AI", "创业", "商业模式"],
  "hook_type": "问题式 | 场景式 | 数据式 | 观点式 | 悬念式",
  "structure_pattern": "总-分-总 | 时间线 | 对比式 | Q&A",
  "source_types": ["一手素材", "公开资料", "案例对比"],
  "word_count": 3200,
  "notable": "值得标注的特殊之处(可留空)"
}

元数据是后续统计分析和规律归纳的基础,不可跳过。


Step 3:脚本分析(L1 表层语言)

运行以下分析,提取表层语言特征:

词频分析

  • 高频名词(100 个)
  • 高频动词(50 个)
  • 高频副词(过度使用的副词 = 需要过滤的噪声)

句式分析

  • 平均句长(字符数)
  • 短句(≤15字)占比
  • 长句(≥50字)占比
  • 段落平均句数

标点与格式

  • 破折号 vs 括号的使用比
  • 引号使用场景
  • 小标题平均字数
  • 中英文混用模式

输出:中文产物写入 语言DNA.md;英文产物写入 language-dna.md。内容包含词频表和句式规律总结。


Step 4:结构标注(L2 文章结构)

对每篇文章人工标注结构骨架,记录:

[开头 hook 类型] + [字数]
→ [第一转折点/核心问题引入]
→ [正文结构:总-分 / 对比 / 时间线 / Q&A]
→ [结尾处理方式:收束 / 悬念 / 呼吁 / 自然结束]

归纳后,按内容类型整理为可复用的结构模板,例如:

访谈类模板:

引题段(150-300字)
  → 为什么此时此人值得聊(1句)
  → 关键背景(2-3句)
  → 本篇核心问题(1-2句)
正文 Q&A
  → 每个大话题前有小标题(4-8字)
  → 每小节 3-6 轮对话
结尾
  → 多为自然收束,无刻意升华

输出:中文产物写入 文章结构模板.md;英文产物写入 structure-patterns.md。按内容类型分类。


Step 5:选题与认知框架归纳(L3-L5)

这是最需要深度阅读的部分,无法用脚本替代。

选题逻辑归纳(L3)

  • 他们倾向于在什么时机切入?(早期判断 / 跟进分析 / 事后复盘)
  • 同一话题,他们的切入角度是什么?(当事人视角 / 读者视角 / 系统视角)
  • 什么类型的话题他们不写?

素材策略(L4)

  • 主要依赖哪类素材?(一手观察 / 二手整理 / 数据引用)
  • 权威对象选取标准是什么?
  • 如何处理敏感或争议性信息?
  • 图片作为素材:截图在论证中承担什么角色?(纯配图 vs 承重结构)精确数据是否只存在于截图中?图文之间的协作模式是什么?

认知框架(L5)

  • 该账号/作者对主题的核心假设是什么?
  • 反复出现的核心命题(3-5 条)
  • 他们认为什么是"好对象"、"好作品"?

输出:中文产物写入 写作视角与认知框架.md;英文产物写入 cognitive-framework.md。


Step 6:视觉风格与排版分析(L6)

这一层分析文章的视觉呈现——读者看到的不只是文字,还有图片节奏、字体层级、排版密度。风格复刻如果只复刻文字而忽略视觉,出来的东西"读着像但看着不像"。

配图策略

  • 图文比:每篇文章平均配图数量、图片间距(每隔多少段落出现一张图)
  • 图片类型分布:界面截图 / 数据图表 / 人物照 / 概念示意图 / meme / 纯装饰
  • 首图风格:是否有封面图?风格是实拍、插画还是纯文字排版?
  • 图片来源模式:原创拍摄 / 官方素材 / 网络素材 / AI 生成
  • 图片功能分类(需逐张查看图片内容):证据型(社交截图/对话/评论)/ 演示型(界面/过程/代码输出)/ 数据型(排行榜/图表)/ 叙事推进型(故事转折在图中)/ 情绪型(meme)/ 权威型(论文/人物照)
  • 图文协作模式:文字和图片如何分工?(引导语→截图→解读?截图即论证?文字概括+截图精确?)

排版格式

  • 字号层级:正文字号、标题字号、引用/注释字号(从 HTML font-size 提取)
  • 加粗使用频率:每千字加粗次数、加粗用于强调关键词还是整句
  • 段落长度:平均段落字数、是否有刻意的短段落节奏(如一句一段)
  • 分隔方式:用小标题分段 / 用分隔线 / 用空行 / 用加粗句作为"隐性标题"

色彩与强调

  • 是否使用彩色文字?用于什么场景?(重点标注 / 链接 / 引用)
  • 背景色块的使用:灰底引用框 / 高亮色块 / 代码块样式
  • 整体色调倾向:素净黑白 / 彩色活泼 / 深色主题

提取方法

  • 如有原始 HTML:统计 font-size、font-weight、color、background 属性分布
  • 如仅有 Markdown:从 **(加粗)、##(标题)、>(引用)、![]()(图片)等标记提取排版规律
  • 必做:抽样 5-10 篇文章逐张打开图片,分析图片功能类型和图文协作模式
  • 统计图片数量、位置分布、功能分类占比

输出:中文产物写入 视觉风格指南.md;英文产物写入 visual-style-guide.md。内容包含配图策略、排版规律和色彩使用总结。


Show full SKILL.md (145 more words)Show less
Step 7:蒸馏产物整合

将以上分析整合为一份可直接用于 AI 复刻的文档:

写作 DNA 文档(Writing-DNA.md)
├── 语言特征(来自 L1)
├── 结构模板(来自 L2,按类型分类)
├── 选题判断标准(来自 L3)
├── 素材使用规范(来自 L4)
├── 核心认知框架(来自 L5)
└── 视觉风格指南(来自 L6:配图策略 + 排版 + 色彩)

这份文档应满足:给任何一个没读过该账号/作者的人,他读完下笔能写出 70 分的近似风格文章——不仅文字像,视觉呈现也像。


四、目录结构规范

(本节说明蒸馏产物的存放位置,写作阶段的使用方式见第六节。)

每个账号或作者目录建议采用以下结构。中文产物使用左侧文件名,英文产物使用括号中的英文文件名:

账号或作者名称/
├── raw/                    # 原始文章语料(.md 格式)
├── _meta/                  # 元数据标注(JSON 或 .md)
├── 语言DNA.md              # English: language-dna.md
├── 文章结构模板.md          # English: structure-patterns.md
├── 写作视角与认知框架.md    # English: cognitive-framework.md
├── 视觉风格指南.md          # English: visual-style-guide.md
├── Writing-DNA.md          # 最终整合文档(可直接嵌入 skill)
└── index.html              # 可选:可视化展示页面

五、质量标准

蒸馏产物完成后,用以下标准自检:

  • 给 AI 喂入 Writing-DNA.md,能否写出该账号/作者风格的文章(评分 ≥7/10)
  • L2 结构模板覆盖了该账号/作者至少 3 种内容类型
  • L5 认知框架提炼出至少 3 条非显而易见的核心命题
  • 元数据覆盖至少 80% 的语料文章
  • L6 视觉分析覆盖配图策略、排版格式、色彩使用三个维度
  • Writing-DNA.md 单文档字数控制在 4000 字以内(过长 = 没蒸馏干净)

六、使用蒸馏产物写作

蒸馏完成后,每次按该 DNA 写作前,必须先完成下面的读取步骤。不允许只凭 Writing-DNA.md 或凭上一轮对话的记忆下笔——整合文档是压缩后的结论,具体的语感、句子长短、过渡方式和标点习惯只存在于分层产物和原文里。

6.1 每次写作前必读

第一步:读完全部蒸馏产物(四份分层产物 + 整合文档,一份都不能跳过)

读什么中文文件名英文文件名提取什么
L1 语言语言DNA.mdlanguage-dna.md高频词、句长分布、标点习惯、中英混用方式
L2 结构文章结构模板.mdstructure-patterns.md匹配本次体裁的结构模板
L3-L5 认知写作视角与认知框架.mdcognitive-framework.md切入角度、素材偏好、核心命题
L6 视觉视觉风格指南.mdvisual-style-guide.md配图位置与类型、加粗密度、段落节奏、分隔方式
整合Writing-DNA.mdWriting-DNA.md总体约束与优先级

第二步:读 5 篇相关的 raw 原文

从 raw/ 中选 5 篇与本次写作体裁和题材最接近的文章通读。选取方式:

  1. 优先用 _meta/ 的 article_type 和 topic_tags 筛选匹配项
  2. 匹配项超过 5 篇时,取时间最近的 5 篇(近期文章更代表当前风格)
  3. 匹配项不足 5 篇时,用同体裁不同题材的文章补齐到 5 篇
  4. _meta/ 不完整或缺失时,直接按文件名中的日期和标题判断

读 raw 的目的不是找素材,而是校准分层产物里描述不出来的东西:句子的实际呼吸感、段落之间怎么接、什么时候突然用一个短句、口语和书面语怎么混。读完要能说出这 5 篇的共同语感,再开始写。

6.2 写作时的优先级

规则冲突时按此顺序取舍:

  1. 用户的明确指令(本次要求的题材、长度、平台、语言)
  2. L2 结构模板中匹配当前体裁的那一套
  3. L1 语言特征与 L6 视觉风格
  4. L3-L5 认知框架(决定观点立场和素材选择,不决定句式)

原文里的具体观点和事实不能直接搬进新文章——复刻的是写法,不是内容。

6.3 写完之后:清理 AI 痕迹

写作完成后,用 skills/lieflat-less-ai-tone/ 的规则清理成稿中的 AI 痕迹。它采用白名单式改写,只处理规则清单内的问题,不改文章框架,也不覆盖本次写作已遵循的 DNA 特征。

蒸馏产物与去 AI 味规则冲突时,以蒸馏产物为准——那是目标作者的真实写法,不是 AI 痕迹。

© larashero3-dotcom, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. 1 hidden character (zero-width or bidirectional) removed. Raw file

Files

SKILL.md and 41 other files (references, assets) in the repository root of larashero3-dotcom/writing-dna-skill.

  • SKILL.md
  • .gitignore
  • CONTRIBUTING.md
  • LICENSE
  • README.en.md
  • README.md
  • agents/openai.yaml
  • assets/writing-dna-hero-en.png
  • assets/writing-dna-hero-zh.png
  • docs/release-checklist.md
  • docs/usage-boundaries.md
  • examples/format-only/README.md
  • examples/format-only/_meta/.gitkeep
  • examples/format-only/raw/.gitkeep
  • … and 28 more

Open the folder on GitHubat commit ee3d97e

Compare with similar skills

Writing DNA Distiller next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Writing DNA Distiller compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Writing DNA Distiller this skilllarashero3-dotcom/writing-dna-skill2.4k—~1.8kAutomated safety check: WarnMIT
Avoid AI Writingconorbronsdon/avoid-ai-writing4.9k3 repos~8.1kAutomated safety check: PassMIT
BrandOhh-889/skyroc79513 repos~733Automated safety check: PassMIT
Khazix WeChat Article WriterKKKKhazix/khazix-skills21k1 repos~2.9kAutomated safety check: PassMIT
Writing Guidelinesvercel-labs/agent-skills32k7 repos~309Automated safety check: PassNone
Unslop AI Writing Cleanuptheclaymethod/unslop518—~1.7kAutomated safety check: PassMIT

Similar skills

  • Avoid AI Writing

    conorbronsdon/avoid-ai-writing

    Audit and rewrite content to remove AI writing patterns ("AI-isms").

    4.9k GitHub starsUsed in 3 repos~8.1k tokens
    Writing & ContentAuto-check passed
  • Brand

    Ohh-889/skyroc

    Brand voice, visual identity, messaging frameworks, asset management, brand consistency.

    795 GitHub starsUsed in 13 repos~733 tokens
    Writing & ContentAuto-check passed
  • Khazix WeChat Article Writer

    KKKKhazix/khazix-skills

    Writes long-form WeChat official account articles in the personal style of the Khazix account, from briefs, links, PDFs or rough notes, with a topic quality check.

    21k GitHub starsUsed in 1 repo~2.9k tokens
    Writing & ContentAuto-check passed
  • Writing Guidelines

    vercel-labs/agent-skills

    Official

    Review docs/prose for Writing Guidelines compliance. An agent skill from vercel-labs/agent-skills.

    32k GitHub starsUsed in 7 repos~309 tokens
    Writing & ContentAuto-check passed
  • Unslop AI Writing Cleanup

    theclaymethod/unslop

    Removes AI writing tells from prose through an audit-first flow, routing to a two-pass rewrite, a report-only cleanup, voice teaching or mimicry depending on the sub-command used.

    518 GitHub stars~1.7k tokensUpdated 1 mo ago
    Writing & ContentAuto-check passed
  • UX Writing

    content-designer/ux-writing-skill

    Applies UX writing practice to interface copy such as buttons, errors, forms and onboarding, using four quality standards and accessibility guidance.

    224 GitHub starsUsed in 1 repo~3.8k tokens
    Writing & ContentAuto-check passed

More from larashero3-dotcom/writing-dna-skill

  • AI Writing Tell Remover

    larashero3-dotcom/writing-dna-skill

    Rewrites only the sentences that match an explicit whitelist of AI writing tells, leaving everything else, including document structure and unmatched text, exactly as written.

    2.4k GitHub stars~2.8k tokensUpdated 1 mo ago
    Auto-check passed

Questions about Writing DNA Distiller

What does Writing DNA Distiller do?

Distills a reusable Writing DNA from at least 20 complete articles by one author, account or brand, covering language, structure, topics, sources, thinking and visuals. md` file. The aim is a set of operational rules rather than a summary, usable to understand an author's perspective, to imitate the style and to compare how different authors treat the same issue.

When should I use Writing DNA Distiller?

Writing DNA Distiller fits situations like: analyzing the writing style of an author or publication from past articles; preparing a style guide so new posts match an existing brand voice; comparing how two authors approach the same topic.

How do I install Writing DNA Distiller in Claude Code?

Run `npx skills add larashero3-dotcom/writing-dna-skill --skill writing-dna-skill -a claude-code`. Or copy the skill folder (the larashero3-dotcom/writing-dna-skill repository) into .claude/skills/writing-dna-skill in your project. Claude Code loads it when a task matches its description.

How do I install Writing DNA Distiller in Codex?

Run `npx skills add larashero3-dotcom/writing-dna-skill --skill writing-dna-skill -a codex`. Or copy the skill folder (the larashero3-dotcom/writing-dna-skill repository) into .agents/skills/writing-dna-skill in your project. Codex loads it when a task matches its description.

Can I use Writing DNA Distiller in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add larashero3-dotcom/writing-dna-skill --skill writing-dna-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/writing-dna-skill, .gemini/skills/writing-dna-skill, .github/skills/writing-dna-skill and .opencode/skills/writing-dna-skill in your project.

What does Writing DNA Distiller need to run?

SKILL.md names no scripts, command-line tools or credentials: Writing DNA Distiller is instructions for the agent only. Our summary lists: At least 20 complete articles saved as .md or .txt files.

Does Writing DNA Distiller access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Writing DNA Distiller safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): contains zero-width characters. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Writing DNA Distiller use?

Writing DNA Distiller is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Writing DNA Distiller use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Writing DNA Distiller?

Skills that share tags, products or a category with Writing DNA Distiller: Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), Brand (Ohh-889/skyroc, 795 stars), Khazix WeChat Article Writer (KKKKhazix/khazix-skills, 21k stars) and Writing Guidelines (vercel-labs/agent-skills, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Writing DNA Distiller?

larashero3-dotcom (a GitHub user) maintains it in larashero3-dotcom/writing-dna-skill, which has 2,363 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on August 24, 2026.

Source: larashero3-dotcom/writing-dna-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.