x-create

仓库: kangarooking/x-skills
安装量: 40
排名: #18098

安装

npx skills add https://github.com/kangarooking/x-skills --skill x-create
X Create
Create viral X posts (short tweets, threads, replies) based on user's persona and post patterns.
First-Time Setup
Check user profile before creating content:
Read
references/user-profile.md
If
initialized: false
or file doesn't exist → Run onboarding
If
initialized: true
→ Proceed to content creation
Onboarding Questions
Ask user these questions using AskUserQuestion tool:
账号定位（领域）
你的X账号主要分享什么内容？
Options: AI/科技, 创业/商业, 个人成长, 投资理财, Other
目标受众
你的目标读者是谁？
Options: 中文用户, 英文用户, 双语用户
人设风格
你希望塑造什么样的人设？
Options: 专业严肃, 轻松幽默, 犀利观点, 温暖亲和, Other
After collecting answers, update
references/user-profile.md
with
initialized: true
.
Post Types
5 Categories
Type
Style
Use When
Intent Signals (路由线索)
高价值干货
信息密度高，可收藏
教程、工具推荐、方法论
目标是收藏/转发；强调可执行清单、工具、步骤
犀利观点
有态度有立场
行业评论、反常识观点
目标是讨论/对立；需要强立场、对比、反常识
热点评论
快速反应
新闻评论、事件点评
目标是蹭热度/抢时效；围绕刚发生事件快速解读
故事洞察
个人经历+洞察
案例分析、经验复盘
目标是共鸣/关注；用具体场景+转折+金句
技术解析
深度技术
原理讲解、源码分析
目标是建立专业度；解释原理、机制、影响与建议
Output Formats
短推文
(≤280 characters) - Single tweet
Thread
(多条串联) - 3-10 tweets connected
评论回复
- For replying to trending posts
Creation Workflow
Step 1: Load Context
1. Read references/user-profile.md → Get persona, style
2. (Optional) Read state from ~/.claude/skills/x-create/state/
- liked_topics.json (positive samples)
- rejected_topics.json (negative samples)
- events.jsonl (optional)
3. Check assets/templates/{type}/ → Look for user reference posts
4. If no references → Use default patterns from references/post-patterns.md
Step 2: Intent-based Routing
Determine intent first, then choose style and format:
Intent → Style (5 categories)
收藏/转发导向 → 高价值干货
讨论/对立导向 → 犀利观点
时效/热点导向 → 热点评论
共鸣/关注导向 → 故事洞察
专业/技术导向 → 技术解析
Style → Output format
Short tweet
Single insight, quick take, one-liner
Thread
Multi-point analysis, step-by-step, detailed breakdown
Reply
Designed to respond to specific post/topic
If user explicitly provides
--type
, follow it. Otherwise route automatically.
Step 3: Apply Pattern
Read
references/post-patterns.md
for the specific post type pattern.
Step 4: Generate Content (A/B Variants)
Create
two variants
by default:
Variant A
More direct, stronger hook, higher contrast
Variant B
More structured, more evidence, slightly more neutral Follow: User's persona style Selected post style pattern Reference examples (if available) Step 4.5: Humanize Pass（去 AI 味，默认必做） For each variant, rewrite the text to sound like a real person on X while keeping meaning and claims unchanged: Delete filler + chatbot politeness: avoid "当然/希望这对你有帮助/让我们来深入探讨" Remove grand/marketing tone: avoid "标志着/至关重要/不断演变的格局/彰显/赋能/令人叹为观止" No vague attribution: avoid "专家认为/行业报告显示" unless you provide a specific source; otherwise rewrite as "我观察到/我的判断是..." Reduce connective phrases: avoid overusing "此外/然而/因此"; prefer simple sentences and line breaks Break formula: do not force "三段式"; 2 points is fine; mix short + long sentences Avoid dash spam: do not stack "——" Prefer concrete details over empty conclusions; if you are unsure, say it plainly and briefly Thread constraints: Each tweet must be <= 280 characters Do not make every tweet identical in structure; allow 1-2 short "pause" lines Step 5: Critic (Self-evaluation) + Rewrite Once Score the humanized Variant A/B as the target reader (0-10): Hook strength Information density / value Clarity and readability Credibility (no exaggeration / no made-up facts) Persona fit Action likelihood: like / repost / bookmark / reply "AI 味" control: no empty grand statements, no templated endings, no vague authority Rules: If both Variant A and B score < 7, rewrite once (produce A2/B2), then run the same humanize pass again , and re-score. Select the best variant as final output, but still show both drafts. Output Format

推文创作

选题

推文类型

风格

Drafts

Variant A {For short tweet: single tweet content}

1/N

2/N {second tweet} ...

N/N
{final tweet with call to action}
**
Critic score (0-10)
**
{critic_score_a}

Variant B {For short tweet: single tweet content}

1/N

2/N {second tweet} ...

N/N
{final tweet with call to action}
**
Critic score (0-10)
**
{critic_score_b}

Selected Selected variant: {A|B|A2|B2} Reason: {one-sentence reason}

发布建议

最佳发布时间:

配图建议:

预期互动:
下一步：运行 /x-publish 发布到草稿箱
Append machine-readable blocks for hooks/state ingestion:
CREATE_JSON
{
"schema_version"
:
"x_skills.create.v1"
,
"topic"
:
"{topic}"
,
"post_type"
:
"short|thread|reply"
,
"post_style"
:
"high-value|sharp-opinion|trending-comment|story-insight|tech-analysis"
,
"variants"
:
[
{
"id"
:
"A"
,
"critic_score_0_10"
:
0
,
"text"
:
"..."
}
,
{
"id"
:
"B"
,
"critic_score_0_10"
:
0
,
"text"
:
"..."
}
]
,
"selected"
:
"A|B|A2|B2"
,
"rewrite_once"
:
true
}
HOOKS_JSON
{
"schema_version"
:
"x_skills.hooks.v1"
,
"topic"
:
"{topic}"
,
"hooks"
:
[
{
"text"
:
"..."
,
"source"
:
"variant.A"
,
"tags"
:
[
"数字|反常识|痛点|悬念|类比"
]
,
"score_0_10"
:
0
}
]
}
Template Priority
User templates first
Check
assets/templates/{type}/
Default patterns
Use references/post-patterns.md Example: Creating 高价值干货 post: 1. Check assets/templates/high-value/ 2. If files exist → Learn style from examples 3. If empty → Use default pattern from post-patterns.md Resources references/user-profile.md User customization info (shared across all x-skills) references/post-patterns.md Default viral post patterns for 5 categories assets/templates/ User-provided reference posts organized by type: high-value/ - 高价值干货类参考 sharp-opinion/ - 犀利观点类参考 trending-comment/ - 热点评论类参考 story-insight/ - 故事洞察类参考 tech-analysis/ - 技术解析类参考 Example User: /x-create Claude 4.5 Opus发布 --type thread Read user-profile.md → persona: 专业严肃、犀利观点 Check assets/templates/tech-analysis/ → empty Read post-patterns.md → Get tech-analysis pattern Generate thread:

1/5

Claude 4.5 Opus 上线了。我先说结论：它更像“慢一点，但更稳”的那类模型。 我用 3 个小任务试了下，写个线程记录👇

2/5

我最直观的感受不是“更聪明”，而是更会停下来检查自己。 同一个问题，它更少给“听起来对”的答案。

3/5

三个场景（都不算大项目）： 1) 重构一个旧模块：更愿意先问清边界，再动手改 2) 复杂推理题：会把关键假设写出来（这点很救命） 3) 长文档梳理：更少漏掉前后矛盾的地方

4/5

代价也很现实： - 反应慢一点 - 成本可能更高（看你用的套餐/调用方式） - 你得给它更明确的上下文

5/5

如果你做的是“错一次就很麻烦”的任务（代码、决策、长文整理），值得试。 只是日常闲聊，感知没那么强。你们试过了吗？ Integration After creation, suggest: 推文创作完成！ - 类型: {thread/short/reply} - 字数: {word_count} - 预计阅读: {read_time} 下一步：运行 /x-publish 发布到X草稿箱 （反馈闭环，可选） - 采纳并进入正样本： python ~/.claude/skills/x-create/scripts/x_state.py like --topic-json '{"title":"{topic}","selected":"{A|B}","critic_score":8}' - 否决并进入负样本： python ~/.claude/skills/x-create/scripts/x_state.py reject --topic-json '{"title":"{topic}","reason":"low_value"}' - 写入事件（hooks 自动收集也可用）： python ~/.claude/skills/x-create/scripts/x_state.py event --event create.generated --payload-json '{"topic":"{topic}","variants":["A","B"],"selected":"{A|B}"}'

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