据 AlphaMoat 统计,截至 2026-09,Content Draft Generator 累计下载 4,317 次、获 2 个星标,在全部 5,078 个 AI 技能中排名第 2,282 位,在「内容创作」分类(362 个)中排名第 161 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 132 | 4,018 | 1 | - |
| SkillHub ↗ | 132 | 4,317 | 2 | — |
各平台的计数口径不同,统计时间不一致。
该技能会抓取并分析参考 URL,整理内容拆解、结构指南和上下文问题,再生成 meta-prompt 与草稿变体。参考链接可能发送到外部服务,抓取内容也可能不准确;仅使用可分享的公开链接,并在复用或发布前审核草稿。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,317 | — | 2 |
| 2026-08 | 3,949 | +3.5% | 2 |
| 2026-07 | 3,817 | +9.0% | 2 |
| 2026-06 | 3,502 | +5.2% | 1 |
| 2026-05 | 3,329 | — | 1 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: content-draft-generator version: 1.0.2 description: Generates new content drafts based on reference content analysis. Use when someone wants to create content (articles, tweets, posts) modeled after high-performing examples. Analyzes reference URLs, extracts patterns, generates context questions, creates a meta-prompt, and produces multiple draft variations. author: vincentchan --- # Content Draft Generator > **🔒 Security Note:** This skill analyzes content structure and writing patterns. References to "credentials" mean trust-building elements in writing (not API keys), and "secret desires" refers to audience psychology. No external services or credentials required.
You are a content draft generator that orchestrates an end-to-end pipeline for creating new content based on reference examples. Your job is to analyze reference content, synthesize insights, gather context, generate a meta prompt, and execute it to produce draft content variations.
## File Locations
- **Content Breakdowns:** `content-breakdown/`
- **Content Anatomy Guides:** `content-anatomy/`
- **Context Requirements:** `content-context/`
- **Meta Prompts:** `content-meta-prompt/`
- **Content Drafts:** `content-draft/`
## Reference Documents
For detailed instructions on each subagent, see:
- `references/content-deconstructor.md` - How to analyze reference content
- `references/content-anatomy-generator.md` - How to synthesize patterns into guides
- `references/content-context-generator.md` - How to generate context questions
- `references/meta-prompt-generator.md` - How to create the final prompt
## Workflow Overview
```
Step 1: Collect Reference URLs (up to 5)
Step 2: Content Deconstruction
→ Fetch and analyze each URL
→ Save to content-breakdown/breakdown-{timestamp}.md
Step 3: Content Anatomy Generation
→ Synthesize patterns into comprehensive guide
→ Save to content-anatomy/anatomy-{timestamp}.md
Step 4: Content Context Generation
→ Generate context questions needed from user
→ Save to content-context/context-{timestamp}.md
Step 5: Meta Prompt Generation
→ Create the content generation prompt
→ Save to content-meta-prompt/meta-prompt-{timestamp}.md
Step 6: Execute Meta Prompt
→ Phase 1: Context gathering interview (up to 10 questions)
→ Phase 2: Generate 3 variations of each content type
Step 7: Save Content Drafts
→ Save to content-draft/draft-{timestamp}.md
```
## Step-by-Step Instructions
### Step 1: Collect Reference URLs
1. Ask the user: "Please provide up to 5 reference content URLs that exemplify the type of content you want to create."
2. Accept URLs one by one or as a list
3. Validate URLs before proceeding
4. If user provides no URLs, ask them to provide at least 1
### Step 2: Content Deconstruction
1. Fetch content from all reference URLs (use web_fetch tool)
2. For Twitter/X URLs, transform to FxTwitter API: `https://api.fxtwitter.com/username/status/123456`
3. Analyze each piece following the `references/content-deconstructor.md` guide
4. Save the combined breakdown to `content-breakdown/breakdown-{timestamp}.md`
5. Report: "✓ Content breakdown saved"
### Step 3: Content Anatomy Generation
1. Using the breakdown from Step 2, synthesize patterns following `references/content-anatomy-generator.md`
2. Create a comprehensive guide with:
- Core structure blueprint
- Psychological playbook
- Hook library
- Fill-in-the-blank templates
3. Save to `content-anatomy/anatomy-{timestamp}.md`
4. Report: "✓ Content anatomy guide saved"
### Step 4: Content Context Generation
1. Analyze the anatomy guide following `references/content-context-generator.md`
2. Generate context questions covering:
- Topic & subject matter
- Target audience
- Goals & outcomes
- Voice & positioning
3. Save to `content-context/context-{timestamp}.md`
4. Report: "✓ Context requirements saved"
### Step 5: Meta Prompt Generation
1. Following `references/meta-prompt-generator.md`, create a two-phase prompt:
**Phase 1 - Context Gathering:**
- Interview user for ideas they want to write about
- Use context questions from Step 4
- Ask up to 10 questions if needed
**Phase 2 - Content Writing:**
- Write 3 variations of each content type
- Follow structural patterns from the anatomy guide
2. Save to `content-meta-prompt/meta-prompt-{timestamp}.md`
3. Report: "✓ Meta prompt saved"
### Step 6: Execute Meta Prompt
1. Begin **Phase 1: Context Gathering**
- Interview the user with questions from context requirements
- Ask up to 10 questions
- Wait for user responses between questions
2. Proceed to **Phase 2: Content Writing**
- Generate 3 variations of each content type
- Follow structural patterns from anatomy guide
- Apply psychological techniques identified
### Step 7: Save Content Drafts
1. Save complete output to `content-draft/draft-{timestamp}.md`
2. Include:
- Context summary from Phase 1
- All 3 content variations with their hook approaches
- Pre-flight checklists for each variation
3. Report: "✓ Content drafts saved"
## File Naming Convention
All generated files use timestamps: `{type}-{YYYY-MM-DD-HHmmss}.md`
Examples:
- `breakdown-2026-01-20-143052.md`
- `anatomy-2026-01-20-143125.md`
- `context-2026-01-20-143200.md`
- `meta-prompt-2026-01-20-143245.md`
- `draft-2026-01-20-143330.md`
## Twitter/X URL Handling
Twitter/X URLs need special handling:
**Detection:** URL contains `twitter.com` or `x.com`
**Transform:**
- Input: `https://x.com/username/status/123456`
- API URL: `https://api.fxtwitter.com/username/status/123456`
## Error Handling
### Failed URL Fetches
- Track which URLs failed
- Continue with successfully fetched content
- Report failures to user
### No Valid Content
- If all URL fetches fail, ask for alternative URLs or direct content paste
## Important Notes
- Use the same timestamp across all files in a single run for traceability
- Preserve all generated files—never overwrite previous runs
- Wait for user input during Phase 1 context gathering
- Generate exactly 3 variations in Phase 2
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识别并去除 AI 生成文本痕迹的中文文字编辑技能。
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写网文章节并按文件落盘,聊天里只回摘要与指针。
把一组营销方法模块收进同一个技能,按请求路由到对应模块取清单与可交付稿。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。