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: INLINECODE0
• Content Anatomy Guides: INLINECODE1
• Context Requirements: INLINECODE2
• Meta Prompts: INLINECODE3
• Content Drafts: INLINECODE4

Reference Documents

For detailed instructions on each subagent, see:

• - references/content-deconstructor.md - How to analyze reference content
• INLINECODE6 - How to synthesize patterns into guides
• INLINECODE7 - How to generate context questions
• INLINECODE8 - How to create the final prompt

Workflow Overview

CODEBLOCK0

Step-by-Step Instructions

Step 1: Collect Reference URLs

1. 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. 1. Fetch content from all reference URLs (use web_fetch tool)
2. For Twitter/X URLs, transform to FxTwitter API: INLINECODE9
3. Analyze each piece following the references/content-deconstructor.md guide
4. Save the combined breakdown to INLINECODE11
5. Report: "✓ Content breakdown saved"

Step 3: Content Anatomy Generation

1. 1. Using the breakdown from Step 2, synthesize patterns following INLINECODE12
2. Create a comprehensive guide with:

- Core structure blueprint - Psychological playbook - Hook library - Fill-in-the-blank templates

1. 3. Save to INLINECODE13
2. Report: "✓ Content anatomy guide saved"

Step 4: Content Context Generation

1. 1. Analyze the anatomy guide following INLINECODE14
2. Generate context questions covering:

- Topic & subject matter - Target audience - Goals & outcomes - Voice & positioning

1. 3. Save to INLINECODE15
2. Report: "✓ Context requirements saved"

Step 5: Meta Prompt Generation

1. 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. 2. Save to INLINECODE17
2. Report: "✓ Meta prompt saved"

Step 6: Execute Meta Prompt

1. 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

1. 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. 1. Save complete output to INLINECODE18
2. Include:

- Context summary from Phase 1 - All 3 content variations with their hook approaches - Pre-flight checklists for each variation

1. 3. Report: "✓ Content drafts saved"

File Naming Convention

All generated files use timestamps: INLINECODE19

Examples:

• - INLINECODE20
• INLINECODE21
• INLINECODE22
• INLINECODE23
• INLINECODE24

Twitter/X URL Handling

Twitter/X URLs need special handling:

Detection: URL contains twitter.com or INLINECODE26

Transform:

• - Input: INLINECODE27
• API URL: INLINECODE28

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