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Agent Skill · 待分类

style-writer(风格作家)

style-writer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

style-writer 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 10,303。

总安装 210周安装 9GitHub Stars 37下载 73核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:style-writer(风格作家)
来源仓库:https://github.com/majesticlabs-dev/majestic-marketplace
仓库路径:skills/style-writer
安装命令:
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill style-writer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill style-writer

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态进行协作整理。通过 npx skills add 命令从指定仓库安装使用。建议确认权限范围和维护状态,避免触发联网或文件读写操作。

style-writer 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/style-writer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

style-writer 怎么安装?

在终端执行 npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill style-writ…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

style-writer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

style-writer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

style-writer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

style-writer 用的人多吗?

公开数据是累计安装 210 次,近一周安装 9 次,下载 73 次,GitHub 37 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

style-writer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
style-writer

风格作家 · 本页

21037只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Style Writer

Write an article on: $ARGUMENTS

Audience: Content creators with a Style DNA or brand voice report who need new articles written in that exact voice.

Goal: Produce articles that match a measured voice fingerprint precisely — hitting the numbers, not approximating.


Phase 1: Load the Style DNA

Read the style-dna.md file specified by the user. Extract and internalize:

  1. Hard metrics from the Quick Reference Card (sentence length, short ratio, comma density, paragraph length, etc.)
  2. Punctuation rules (what's used, what's forbidden)
  3. Signature devices with their frequencies (fragment stacking, conjunction openers, landing patterns, etc.)
  4. Structural blueprint (opening pattern, body organization, closing pattern)
  5. Tone profile (POV, hedging placement, emotional register)
  6. Banned patterns if listed
  7. Vocabulary character (lexical diversity, thematic anchoring terms, accessibility level)

If the DNA file has a Cross-Article Comparison with multiple modes (e.g., "workshop tour" vs. "war story"), determine which mode fits the requested topic and target word count. State which mode you're using and why.


Phase 2: Plan the Article

Before writing a single sentence, build a skeleton:

Core thesis

State the single boldest, most specific claim about this topic in one sentence. This becomes your opening.

Historical anchor or analogy

What prior shift, pattern, or concrete comparison grounds this piece? Identify it.

Specifics inventory

List the concrete details you'll use:

  • 2-4 named companies, people, or products
  • 3-5 specific numbers, dollar amounts, or data points
  • 1 attributed quote (if available and natural)
  • 2-3 concrete scenarios or examples

Section plan

Outline 3-5 headed sections. For each, note:

  • Section thesis (1 sentence)
  • Key evidence or example
  • Landing sentence or fragment

Opening and closing

Plan the first 3-4 paragraphs and last 3-4 paragraphs according to the structural blueprint from the DNA.

Present the plan to the user and wait for approval before drafting.


Phase 3: Draft the Article

Write the full article following the plan. While drafting, actively manage these constraints:

Rhythm management

  • After every 2-3 sentences in the 16-25 word range, drop one in the 1-7 range
  • Never stack more than 2 long sentences (26+) consecutively
  • Use fragment stacking at the frequency specified in the DNA
  • Hit the target sentence length distribution across the full piece

Punctuation compliance

  • Use ONLY the punctuation marks the DNA permits
  • If em dashes are zero in the DNA, use zero em dashes. No exceptions.
  • Hit the target comma density (check after drafting)
  • Use colons, semicolons, and parentheticals at the DNA's measured frequency

Device placement

  • Place signature devices at their measured frequency
  • Distribute conjunction openers (And/But/Or/So) evenly, not clustered
  • Place rhetorical questions where the DNA indicates (section openers? clusters? dismissals?)
  • Use landing patterns ("That's...", fragments, one-sentence paragraphs) at section closes

Tone calibration

  • Match the POV (first person singular? plural? mixed?)
  • Place hedges on the same type of claims the DNA shows (predictions? data? never on thesis?)
  • Match the emotional register (profanity only if DNA shows it, and only at equivalent intensity points)
  • Use contractions at the DNA's measured rate

Vocabulary

  • Keep lexical diversity near the DNA's target
  • Repeat key topic terms deliberately (thematic anchoring), don't synonym-hunt
  • Match the long-word percentage
  • Use the same accessibility level: if the DNA shows accessible vocabulary, don't go academic

Phase 4: Self-Audit

After completing the draft, run a verification pass. For each metric, compare your draft against the DNA target:

Metrics to check

Use Python or manual counting to measure your draft:

MetricDNA TargetYour DraftAccuracy
Avg sentence length
Short sentence ratio (<8 words)
Comma density per 100w
Colon density per 100w
Semicolons
Em/en dashes
One-sentence paragraph %
Avg paragraph length (words)
Conjunction openers %
Rhetorical questions (count)
Parenthetical asides (count)
Contractions per 100w
You/your per 100w
I/my/me per 100w
Exclamation marks

Accuracy scoring

For each metric, calculate accuracy as:

accuracy = 100 - abs(target - actual) / target * 100

Clamp to 0-100%. Report the average across all metrics.

Fix pass

If any metric is below 80% accuracy:

  1. Identify which sentences or paragraphs are pulling the metric off target
  2. Revise those specific passages
  3. Re-measure to confirm improvement

Do NOT present the draft until the average accuracy is above 85% and no single metric is below 70%.


Phase 5: Present the Draft

Show the user:

  1. The article in full
  2. The accuracy table (side-by-side comparison of DNA targets vs. draft metrics with accuracy percentages)
  3. Overall accuracy score (average of all metric accuracies)
  4. Device checklist noting which signature devices were used and their counts

Then ask:

Article ready at [X]% overall style accuracy. Want me to save it, or revise specific sections?

Wait for the user's direction before saving.


Execution Notes

  • If the user doesn't specify a style-dna.md file, check for any *-style-dna.md files in the current directory and docs/. Ask which one to use.
  • If multiple DNA files exist for the same author, prefer the one from the longer source article (it captures the fuller voice).
  • Target word count: match the source article's length unless the user specifies otherwise.
  • Never sacrifice readability to hit a metric. If hitting a number makes a sentence awkward, prioritize natural flow and note the deviation.
  • The banned phrases list is absolute. Zero tolerance. Check every sentence against it.

Integration

Works with the content creation pipeline:

style-forensics (create DNA) → style-writer (write in that voice) → humanizer (with same DNA, strip AI tells) → copy-editor (polish)
  • Before style-writer: style-forensics to create the Style DNA report from writing samples
  • After style-writer: humanizer to strip any remaining AI patterns, copy-editor for final polish
  • Instead of style-writer: content-writer for general articles without a voice target, seo-content for SEO-first articles

平台分布

Codex

36.06%
按下载量换算26

Claude

33.13%
按下载量换算24

Cursor

17.12%
按下载量换算12

Gemini CLI

9%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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