From sundial-org-awesome-openclaw-skills-4
Generates content drafts (articles, tweets, posts) by analyzing reference URLs, extracting patterns, generating context questions, creating meta-prompts, and producing variations modeled after high-performers.
npx claudepluginhub joshuarweaver/cascade-ai-ml-agents-misc-2 --plugin sundial-org-awesome-openclaw-skills-4This skill uses the workspace's default tool permissions.
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.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Generates original PNG/PDF visual art via design philosophy manifestos for posters, graphics, and static designs on user request.
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.
content-breakdown/content-anatomy/content-context/content-meta-prompt/content-draft/For detailed instructions on each subagent, see:
references/content-deconstructor.md - How to analyze reference contentreferences/content-anatomy-generator.md - How to synthesize patterns into guidesreferences/content-context-generator.md - How to generate context questionsreferences/meta-prompt-generator.md - How to create the final promptStep 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
https://api.fxtwitter.com/username/status/123456references/content-deconstructor.md guidecontent-breakdown/breakdown-{timestamp}.mdreferences/content-anatomy-generator.mdcontent-anatomy/anatomy-{timestamp}.mdreferences/content-context-generator.mdcontent-context/context-{timestamp}.mdreferences/meta-prompt-generator.md, create a two-phase prompt:Phase 1 - Context Gathering:
Phase 2 - Content Writing:
content-meta-prompt/meta-prompt-{timestamp}.mdBegin Phase 1: Context Gathering
Proceed to Phase 2: Content Writing
content-draft/draft-{timestamp}.mdAll generated files use timestamps: {type}-{YYYY-MM-DD-HHmmss}.md
Examples:
breakdown-2026-01-20-143052.mdanatomy-2026-01-20-143125.mdcontext-2026-01-20-143200.mdmeta-prompt-2026-01-20-143245.mddraft-2026-01-20-143330.mdTwitter/X URLs need special handling:
Detection: URL contains twitter.com or x.com
Transform:
https://x.com/username/status/123456https://api.fxtwitter.com/username/status/123456