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

   這個技能的最新版本可以在7w4.net小蔥技能站找到。

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:
3. Core structure blueprint
4. Psychological playbook
5. Hook library
6. Fill-in-the-blank templates
7. Save to content-anatomy/anatomy-{timestamp}.md
8. 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:
3. Topic & subject matter
4. Target audience
5. Goals & outcomes
6. Voice & positioning
7. Save to content-context/context-{timestamp}.md
8. 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

1. Save to content-meta-prompt/meta-prompt-{timestamp}.md
2. Report: "✓ Meta prompt saved"

Step 6: Execute Meta Prompt

1. Begin Phase 1: Context Gathering
2. Interview the user with questions from context requirements
3. Ask up to 10 questions

4. Wait for user responses between questions

5. Proceed to Phase 2: Content Writing

6. Generate 3 variations of each content type
7. Follow structural patterns from anatomy guide
8. Apply psychological techniques identified

Step 7: Save Content Drafts

1. Save complete output to content-draft/draft-{timestamp}.md
2. Include:
3. Context summary from Phase 1
4. All 3 content variations with their hook approaches
5. Pre-flight checklists for each variation
6. 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

這個 Skill 質量不錯，幫你把寫得好的內容當作參考，自動生成類似風格的新內容。整個流程設計清晰，生成3種不同版本給你挑，不用自己費力模仿。缺點是缺少實際例子看效果，生成的內容好不好主要看你提供的參考材料質量如何。適合想快速產出大量風格統一內容的人用。