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style-writer风格作家

Agent Skill

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。

总安装

210

周安装

9

GitHub Stars

37

下载量

73
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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