Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
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.
skill openclawclawhub Free
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.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/analyze_voice.py, scripts/generate_post.py, references/post-types.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- gravyxbt
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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 cd /data/workspace/skills/x-voice-match python3 scripts/analyze_voice.py @username [--tweets 50] [--output profile.json] Step 2: Generate posts python3 scripts/generate_post.py --profile profile.json --topic "your topic" [--count 3] Or use the all-in-one approach: 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
Voice Profile (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): # Fetch fresh tweets for analysis ./bird.sh user-tweets @gravyxbt_ -n 50 > recent_tweets.txt python3 scripts/analyze_voice.py --input recent_tweets.txt
Post Type Templates
See references/post-types.md for common X post frameworks: Observations Hot takes Self-deprecating humor Crypto commentary Reaction posts Questions
Update Voice Profile
Re-analyze periodically to capture style evolution: python3 scripts/analyze_voice.py @username --update profile.json
Generate by Post Type
python3 scripts/generate_post.py --profile profile.json --type "hot-take" --topic "crypto"
Batch Generation
python3 scripts/generate_post.py --profile profile.json --batch topics.txt --output posts.json
Workflow
First time: Run full analysis on 30-50 tweets Generate posts: Provide topic, get 3-5 style-matched options User picks: Select best option or iterate with feedback Periodic updates: Re-analyze monthly or after major voice shifts
Tips
Minimum tweets: 30 tweets for basic analysis, 50+ for accuracy Recency matters: Recent tweets reflect current style better than old ones Topic relevance: Generated posts work best on topics the account normally covers Confidence scores: <70% = may not sound authentic, revise or regenerate
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs2 Scripts
- SKILL.md
- references/post-types.md
- scripts/analyze_voice.py
- scripts/generate_post.py