adolf/extensions/open-prose/skills/prose/examples/34-content-pipeline.prose

# Content Creation Pipeline
#
# From idea to published content in one run. Researches a topic in parallel,
# writes a blog post, refines it through editorial review, and generates
# social media posts. Watch an entire content operation happen automatically.
#
# Usage: Provide a topic and watch the content materialize.

input topic: "The topic to create content about"
input audience: "Target audience (e.g., 'developers', 'executives', 'general')"

agent researcher:
  model: opus          # Deep research requires reasoning
  skills: ["web-search"]
  prompt: """
You are a research specialist. For any topic:
1. Find authoritative sources
2. Identify key facts and statistics
3. Note interesting angles and hooks
4. Cite your sources

Return structured research with citations.
"""

agent writer:
  model: opus          # Writing is hard work
  prompt: """
You are a skilled technical writer. You write:
- Clear, engaging prose
- Well-structured articles with headers
- Content appropriate for the target audience
- With a distinctive but professional voice

Avoid jargon unless writing for experts.
"""

agent editor:
  model: sonnet
  persist: true
  prompt: """
You are a senior editor. You review content for:
- Clarity and flow
- Factual accuracy
- Engagement and hook strength
- Appropriate length and structure

Be constructive. Suggest specific improvements.
"""

agent social-strategist:
  model: sonnet
  prompt: """
You create social media content. For each platform:
- Twitter/X: Punchy, hooks, threads if needed
- LinkedIn: Professional, insight-focused
- Hacker News: Technical, understated, genuine

Match the culture of each platform. Never be cringe.
"""

# Phase 1: Parallel research from multiple angles
session "Research phase starting for: {topic}"

parallel:
  core_research = session: researcher
    prompt: """
Deep research on: {topic}

Find:
- Current state of the art
- Recent developments (last 6 months)
- Key players and their positions
- Statistics and data points
"""

  competitive_landscape = session: researcher
    prompt: """
Competitive/comparative research on: {topic}

Find:
- Alternative approaches or solutions
- Pros and cons of different options
- What experts recommend
"""

  human_interest = session: researcher
    prompt: """
Human interest research on: {topic}

Find:
- Real-world case studies
- Success and failure stories
- Quotes from practitioners
- Surprising or counterintuitive findings
"""

# Phase 2: Synthesize research
let research_synthesis = session "Synthesize all research"
  prompt: """
Combine all research into a unified brief:
1. Key thesis/angle for the article
2. Supporting evidence ranked by strength
3. Narrative arc suggestion
4. Potential hooks and headlines

Target audience: {audience}
"""
  context: { core_research, competitive_landscape, human_interest }

# Phase 3: Write first draft
let draft = session: writer
  prompt: """
Write a blog post on: {topic}

Target: {audience}
Length: 1500-2000 words
Structure: Hook, context, main points, examples, conclusion

Use the research provided. Cite sources where appropriate.
"""
  context: research_synthesis

# Phase 4: Editorial loop
session: editor
  prompt: "Beginning editorial review. I'll track revisions."

loop until **the article meets publication standards** (max: 4):
  let critique = resume: editor
    prompt: """
Review this draft critically:
1. What works well?
2. What needs improvement?
3. Specific suggestions (be actionable)
4. Overall verdict: READY / NEEDS_REVISION

Be demanding but fair.
"""
    context: draft

  if **the article needs revision**:
    draft = session: writer
      prompt: """
Revise the article based on editorial feedback.
Address each point specifically.
Maintain what's working well.
"""
      context: { draft, critique }

# Phase 5: Generate social media variants
parallel:
  twitter_content = session: social-strategist
    prompt: """
Create Twitter/X content to promote this article:
1. Main announcement tweet (punchy, with hook)
2. 5-tweet thread extracting key insights
3. 3 standalone insight tweets for later

Include placeholder for article link.
"""
    context: draft

  linkedin_post = session: social-strategist
    prompt: """
Create a LinkedIn post for this article:
- Professional but not boring
- Lead with insight, not announcement
- 150-300 words
- End with genuine question for engagement
"""
    context: draft

  hn_submission = session: social-strategist
    prompt: """
Create Hacker News submission:
- Title: factual, not clickbait, <80 chars
- Suggested comment: genuine, adds context, not promotional

HN culture: technical, skeptical, hates marketing speak.
"""
    context: draft

# Phase 6: Package everything
output article = draft
output social = { twitter_content, linkedin_post, hn_submission }

resume: editor
  prompt: """
Content Pipeline Complete!

Final package:
1. Article: {draft length} words, {revision count} revisions
2. Twitter: thread + standalone tweets
3. LinkedIn: professional post
4. HN: submission ready

Recommended publication order:
1. Publish article
2. HN submission (wait for feedback)
3. Twitter thread
4. LinkedIn (next business day AM)

All files saved to ./content-output/
"""
  context: { draft, twitter_content, linkedin_post, hn_submission }