x-voice-match

Analyze a Twitter/X account's posting style and generate authentic posts that match their voice. Use when the user wants to create X posts that sound like them, analyze their posting patterns, or maintain consistent voice across posts. Works with Bird CLI integration.

View Source SKILL.md

Stars

Installs

Status

ACTIVE

Visibility

PUBLIC

安装方式

直接复制以下提示词，发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店，然后安装 x-voice-match 技能。若已安装，则直接安装 x-voice-match 技能。

Overview

Skill Key: gravyxbt/x-voice-match
Author: gravyxbt
Source Repo: openclaw/skills
Version: -
Source Path: skills/gravyxbt/x-voice-match
Latest Commit SHA: b0b4ac04cd10eb8d139ba2b53b955622e18c27d3

Extracted Content

SKILL.md excerpt

# X Voice Match

Analyze Twitter/X accounts to extract posting patterns and generate authentic content that matches the account owner's unique voice.

## Quick Start

**Step 1: Analyze the account**
```bash
cd /data/workspace/skills/x-voice-match
python3 scripts/analyze_voice.py @username [--tweets 50] [--output profile.json]
```

**Step 2: Generate posts**
```bash
python3 scripts/generate_post.py --profile profile.json --topic "your topic" [--count 3]
```

Or use the all-in-one approach:
```bash
python3 scripts/generate_post.py --account @username --topic "AI agents taking over" --count 5
```

## What It Analyzes

The skill extracts:

- **Length patterns**: Tweet character counts, thread usage, one-liner vs paragraph style
- **Tone markers**: Humor style, sarcasm, self-deprecation, edginess level
- **Topics**: Crypto, AI, tech, memes, personal life, current events
- **Engagement patterns**: QT vs original, reaction tweets, conversation starters
- **Language patterns**: Specific phrases, slang, emoji usage, punctuation style
- **Content types**: Observations, hot takes, memes, threads, questions, personal stories

## Output Format

### Voice Profile (JSON)
```json
{
  "account": "@gravyxbt_",
  "analyzed_tweets": 50,
  "patterns": {
    "avg_length": 85,
    "length_distribution": {"short": 0.6, "medium": 0.3, "long": 0.1},
    "uses_threads": false,
    "humor_style": "self-deprecating, ironic",
    "topics": ["crypto", "AI agents", "memes", "current events"],
    "engagement_type": "reactive QT heavy",
    "signature_phrases": ["lmao", "fr", "based"],
    "emoji_usage": "minimal, strategic",
    "punctuation": "lowercase, casual"
  }
}
```

### Generated Posts
Returns 1-N posts with confidence scores and reasoning.

## Integration with Existing Tools

Works with Bird CLI (`/data/workspace/bird.sh`):
```bash
# Fetch fresh tweets for analysis
./bird.sh user-tweets @gravyxbt_ -n 50 > recent_tweets.txt
python3 scripts/analyze_voice.py --input recent_tweets.txt
```

##...

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