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style-forensics风格取证

Agent Skill

style-forensics 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

242

周安装

10

GitHub Stars

37

下载量

79
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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-forensics(风格取证)
来源仓库:https://github.com/majesticlabs-dev/majestic-marketplace
仓库路径:skills/style-forensics
安装命令:
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill style-forensics
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-forensics

简介

style-forensics 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果时使用。
  • 通过 npx skills add 命令从指定仓库安装,具体用法需结合 README 进一步确认。
  • 安装前建议确认权限范围、维护状态及是否涉及联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Style Forensics

Analyze: $ARGUMENTS

Audience: Writers and content creators who need a precise, measured voice fingerprint for use with style-writer and humanizer.

Goal: Extract quantitative style metrics from writing samples and produce a Style DNA report. Measure, don't guess.


Phase 1: Extract Prose

Strip the file to prose only before measuring anything. Remove:

  • Code blocks (...)
  • Inline code (replace with "CODE")
  • Headings (lines starting with #)
  • Blockquotes (lines starting with >)
  • Horizontal rules (---)
  • Metadata lines (tags, bylines, dates)
  • URLs inside markdown links (keep link text)

Save the cleaned prose to a temp file for all subsequent analysis.

Report: Total prose word count.


Phase 2: Sentence Metrics

Extract individual sentences from the prose. Handle:

  • Decimal numbers (don't split on "4.5")
  • Abbreviations (e.g., i.e.)
  • Quoted strings containing periods

Measure and report:

MetricHow
Total sentencesCount
Average sentence lengthwords / sentences
Median sentence lengthMiddle value of sorted lengths
Min / MaxExtremes
Short sentence ratio% of sentences under 8 words
Sentence length distribution4 bands: 1-7, 8-15, 16-25, 26+ words with counts and percentages

Describe the rhythm pattern: How do short and long sentences alternate? Do short sentences cluster? Are long sentences followed by punchy landings?


Phase 3: Punctuation DNA

Count across the full prose text:

MarkMeasure
CommasTotal and per 100 words
SemicolonsTotal and per 100 words
ColonsTotal and per 100 words
Em dashes (— and –)Total
Exclamation marksTotal
Parenthetical asidesTotal, per 100 words, list each one
Rhetorical questionsTotal, per 100 words, list each one

Identify the punctuation fingerprint: Which marks carry the structural load? What's absent? Note any unusual ratios (e.g., colon-to-semicolon ratio).


Phase 4: Paragraph Structure

MetricHow
Total prose paragraphsCount (exclude pure list paragraphs)
Average paragraph lengthWords
One-sentence paragraph ratio% of paragraphs with 0-1 sentence-ending punctuation

Phase 5: Vocabulary Profile

MetricHow
Total wordsCount alpha-only tokens
Unique wordsCount distinct
Lexical diversityunique / total
Long words (8+ chars)Count and percentage
Common word ratio% that are top-100 English function words
Top 15 long wordsWith frequency counts

Describe the vocabulary character: Academic or accessible? Jargon-heavy or plain? Are key terms repeated deliberately (thematic anchoring) or is vocabulary varied?


Phase 6: Tone Profile

POV and Address

  • Count I/my/me instances (per 100 words)
  • Count we/our instances (per 100 words)
  • Count you/your instances (per 100 words)
  • Determine dominant POV

Hedging Language

Search for: probably, perhaps, maybe, might, could be, I think, kinda, sort of, likely, arguably, roughly, nearly, pretty, fairly, basically, genuinely, honestly, admittedly, I guess, I don't think

Report total, per 100 words, and each instance. Note whether hedges appear on claims, predictions, or data.

Emotional Register

  • Profanity count and context for each instance
  • Exclamation marks (already counted)
  • Describe the overall temperature: restrained, casual, intense, breathless?

Contractions

  • Total count and per 100 words
  • Top 10 most frequent

Phase 7: Signature Devices

Search for and quantify each of these patterns. Not all will be present. Report what IS there and what IS NOT.

Sentence openers

  • Top 15 opening words with counts
  • Conjunction openers (And/But/Or/So): total count, percentage of all sentences, breakdown by word

Fragment patterns

  • List all sentences under 6 words ending in a period
  • Identify fragment stacking (2+ consecutive fragments)
  • Identify single-word sentences

Recurring structures

Search for:

  • "That's..." landing sentences
  • "Here's..." launcher sentences
  • "The [noun] is/was..." authoritative declaratives
  • "Not X. Y." contrast patterns
  • "I just..." casualness markers
  • "Let me..." gear-shift cues
  • "Same with X." stacking
  • Credential references ("I've built/seen/written...")
  • Direct persuasion ("believe me," "face it," "let's be honest")
  • Any other repeated phrase pattern that appears 3+ times

Rhetorical devices

  • Anaphora / repetition patterns
  • Rhetorical question clusters (2+ questions in sequence)
  • Colon setup-payoff structures
  • Historical framing / analogy patterns

Temporal markers

  • Count temporal words (first, then, next, eventually, now, started, etc.)
  • Describe the temporal architecture: chronological? thematic? diary-style?

Phase 8: Structural Blueprint

Describe the macro-structure:

Opening pattern

How does the piece begin? (Bold thesis? Scene setting? Credential stack? Anecdote?)

Body organization

How are sections structured internally? What's the repeating unit?

Closing pattern

How does the piece end? (Call to action? Honest concession? Restatement? Promise?)


Phase 9: Compile the Report

Write the full Style DNA report as a markdown file saved next to the source file, named [source-filename]-style-dna.md.

The report MUST include:

  1. Header with source file, word count, date analyzed
  2. Measured Metrics table (all numbers from phases 2-4)
  3. Sentence Length Distribution table
  4. Vocabulary Profile table with top words
  5. Tone Profile section (POV, hedging, emotional register)
  6. Signature Devices section (only devices that actually appear, with counts and examples)
  7. Structural Blueprint section
  8. Quick Reference Card (code block with all key numbers for at-a-glance use)

If analyzing multiple files by the same author, add a Cross-Article Comparison section with a comparison table and analysis of which traits are stable fingerprints vs. sliding dials.


Execution Notes

  • Run all independent measurements in parallel (sentence analysis, punctuation counts, vocabulary analysis can run simultaneously)
  • Use Python for accurate counting. Shell one-liners are fine for simple counts but Python handles sentence splitting and edge cases better.
  • Do not round aggressively. Report to 1 decimal place for percentages, 2 for per-100-word densities.
  • List concrete examples for every device you identify. Numbers without examples are useless.
  • If a metric reads zero, report it explicitly. Absence is data.

Phase 10: Save Prompt

After presenting the report, ask the user:

Style DNA report ready. Want me to save it as [source-filename]-style-dna.md next to the source file?

Wait for confirmation before writing. If the user says yes, save the full report. If analyzing multiple files, also offer to save the cross-article comparison as a separate file.


Integration

Produces Style DNA reports consumed by other skills:

[writing samples] --> style-forensics --> Style DNA report
                                              |
                                              +--> style-writer (write new content in that voice)
                                              +--> humanizer (preserve style when stripping AI tells)
                                              +--> copy-editor (respect voice during editing)
  • Before style-forensics: Gather 1-5 writing samples (pre-AI preferred)
  • After style-forensics: style-writer to write new content matching the voice
  • Not this skill: brand-voice for qualitative brand guidelines, copy-editor for grammar review

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

36.14%
按下载量换算29

Claude

28.89%
按下载量换算23

Cursor

17.04%
按下载量换算13

Gemini CLI

8.78%
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

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill style-forensics 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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