Agent Skillsmohitagw15856/pm-claude-skills › style-fingerprint

style-fingerprint

GitHub

分析用户已发布的3-5篇文档,提取句式、语气等可复用的写作规则,生成风格卡片并保存至大脑。解决AI文风不像用户的问题,确保后续技能输出符合用户个人语调。

exports/openclaw/style-fingerprint/SKILL.md mohitagw15856/pm-claude-skills

Trigger Scenarios

学习我的写作风格 让输出听起来像我 构建声音档案 抱怨AI草稿不像自己

Install

npx skills add mohitagw15856/pm-claude-skills --skill style-fingerprint -g -y
More Options

Non-standard path

npx skills add https://github.com/mohitagw15856/pm-claude-skills/tree/main/exports/openclaw/style-fingerprint -g -y

Use without installing

npx skills use mohitagw15856/pm-claude-skills@style-fingerprint

指定 Agent (Claude Code)

npx skills add mohitagw15856/pm-claude-skills --skill style-fingerprint -a claude-code -g -y

安装 repo 全部 skill

npx skills add mohitagw15856/pm-claude-skills --all -g -y

预览 repo 内 skill

npx skills add mohitagw15856/pm-claude-skills --list

SKILL.md

Frontmatter
{
    "name": "style-fingerprint",
    "homepage": "https:\/\/mohitagw15856.github.io\/pm-claude-skills\/skill\/style-fingerprint.html",
    "metadata": {
        "openclaw": {
            "emoji": "⭐"
        }
    },
    "description": "Study 3-5 documents the user actually shipped and distil a compact style card — so every skill writes in their voice, not the model's. Use when asked to learn my writing style, make outputs sound like me, build a voice profile, or when a user complains AI drafts don't sound like them. Produces a style card (rhythm, register, structure habits, pet phrases, banned moves) saved to the Brain where every other skill reads it."
}

Style Fingerprint Skill

The #1 complaint about AI drafts is "it doesn't sound like me." This skill fixes it at the root: it studies writing the user has actually shipped, extracts the mechanical, imitable features of their voice, and writes a style card into the Brain — after which every brain-aware skill drafts in their register instead of the model's default.

What This Skill Produces

  • A style card (~200-300 words, structured) capturing the user's voice as reproducible rules, not adjectives
  • Before/after proof: one paragraph rewritten from model-default into the fingerprinted voice, so the user can verify the card works
  • The card saved to brain/knowledge/style.md (with the user's approval), plus a one-line pointer in context.md voice section

Required Inputs

Ask for (if not already provided):

  • 3-5 samples the user wrote and shipped — real emails, updates, PRD sections, posts. More samples of the same genre beat variety. Politely reject samples the user merely approved but didn't write — an edited-by-committee doc fingerprints the committee.
  • The target register if samples span several (exec formal vs team casual) — or fingerprint each as a named variant

Extraction Method

Analyse mechanics, not impressions. For each dimension, extract a rule an imitator could follow:

Dimension What to extract
Sentence rhythm Median sentence length; short-sentence frequency; do they open paragraphs long or punchy?
Register & warmth Contractions? First person singular or plural? Directness of asks ("please could we" vs "let's")
Structure habits Bullets vs prose ratio; headers or none; do they front-load the conclusion (BLUF) or build to it?
Signature moves Recurring phrases, connectors ("net-net", "the short version:"), characteristic openings/closings
Emphasis style Bold? Italics? Caps? Em-dashes vs parentheses? Emoji policy (which ones, where, never)?
Numbers Precision habits ("~40%" vs "42.3%"), units, how they hedge estimates
Banned moves What never appears in their writing (corporate filler, exclamation marks, "I hope this finds you well", passive voice…) — the banned list does more work than the rest combined

Then verify: rewrite one neutral paragraph in the extracted voice and check it against the samples. If it reads generic, the card is adjectives, not rules — extract harder.

Output Format

Style card: [name / register variant] — fingerprinted [date] from [n] samples

Rhythm: [rules] Register: [rules] Structure: [rules] Signature moves: [phrases/patterns, quoted from samples] Emphasis & numbers: [rules] Never: [the banned list] Calibration line: (one sentence from the samples that is peak them — future skills imitate toward this)

Proof — same paragraph, twice:

[model-default version] [fingerprinted version]

📥 Save to Brain: propose writing this card to brain/knowledge/style.md and adding a voice: see knowledge/style.md pointer in context.md. Show the write, get a yes, then use ../professional-brain/scripts/brain_write.py … --commit. Brain-aware skills read context.md voice on every run — the fingerprint takes effect immediately and everywhere.

Quality Checks

  • Every dimension yields a followable rule, not an adjective ("uses 8-14 word sentences, one 3-word sentence per paragraph" — not "punchy")
  • Signature moves are quoted verbatim from the samples
  • The banned list has at least 4 entries — voice is defined by what's absent
  • The proof paragraph is verifiably different from model-default and consistent with the samples
  • The card is ≤300 words — a style card that's an essay never gets applied

Anti-Patterns

  • Do not fingerprint from fewer than 3 samples — you'd be fingerprinting one mood
  • Do not describe voice with adjectives ("professional yet approachable") — extract mechanics
  • Do not merge conflicting registers into one mushy card — name variants ("exec", "team") instead
  • Do not include the user's confidential content in the card — rules and short quoted phrases only
  • Do not overwrite an existing style card silently — diff against it and show what changed

Version History

  • 54fad50 Current 2026-07-19 12:35

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Metadata

Files
0
Version
471c606
Hash
898356b6
Indexed
2026-07-19 12:35

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