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gh-rpiplewar-shipfaster-con…/commands/content-generate-drafts.md
2025-11-30 08:52:57 +08:00

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description
description
Generate 5 content variations for a theme using parallel multi-agent approach

Generate Content Drafts

Arguments

$ARGUMENTS - Theme name from themes-memory.md

Mission

Generate 5 unique content variations for the specified theme by spawning 5 parallel sub-agents, each targeting different cognitive bias combinations and content structures.

Process

Follow the Draft Generator agent instructions (agents/draft-generator.md) to:

  1. Read theme details from themes-memory.md
  2. Spawn 5 parallel sub-agents (CRITICAL: simultaneous, not sequential)
  3. Collect sub-agent outputs (5 variations)
  4. Write to content-drafts.md with proper formatting

Execution Steps

Step 1: Read Theme from themes-memory.md

Target Theme: $ARGUMENTS

Extract:

  • Theme name and problem statement
  • Emotional hook and key insight
  • All 5 content angles
  • Source story excerpts

If theme not found: List available themes and ask user to retry with correct name.

Step 2: Spawn 5 Parallel Sub-Agents

CRITICAL: Use single message with 5 Task tool calls to spawn all sub-agents simultaneously.

Each sub-agent receives self-contained prompt with:

  • Full theme details
  • Specific bias activation strategy
  • Content structure requirements
  • Hook-Content-CTA framework
  • Character limits (280 single or 4-6 tweet thread)

Sub-Agent Assignments:

  1. Bold Statement Generator

    • Biases: Contrast-Misreaction + Authority-Misinfluence
    • Structure: Shocking opening → Contrast → Authority evidence → CTA
  2. Story Hook Generator

    • Biases: Curiosity Tendency + Liking/Loving Tendency
    • Structure: Open-loop question → Personal story → Vulnerability → Resolution
  3. Problem-Solution Generator

    • Biases: Social-Proof + Reciprocation + Reward/Punishment
    • Structure: Problem statement → Social proof → Solution value → Free insight
  4. Data-Driven Generator

    • Biases: Authority + Reason-Respecting + Availability-Misweighing
    • Structure: Surprising stat → Reasoning → Concrete example → Implication
  5. Emotional Lollapalooza Generator

    • Biases: Liking + Stress-Influence + 5+ biases converging
    • Structure: Emotional hook → Stress creation → Relief → Multi-bias activation

Step 3: Quality Check Each Variation

Verify:

  • Content factually accurate (matches source stories)
  • Target biases clearly activated
  • Structure follows assigned format
  • Character limits respected
  • No meta-commentary (pure content)

Step 4: Write to content-drafts.md

Location: /home/rpiplewar/fast_dot_ai/poasting/content-drafts.md

Format:

## Theme: {Theme Name}
**Source:** {Linear Task ID}

### Variation 1: Bold Statement
**Content:**
{Generated content}

**Biases Targeted:** Contrast-Misreaction, Authority-Misinfluence

**Scores:**
[To be filled by Scorer agent]

---

### Variation 2: Story Hook
...

Action: APPEND to file (don't overwrite existing content from other themes)

Validation Checklist

Before marking generation complete:

  • All 5 variations generated
  • Each variation targets DIFFERENT bias combinations
  • All content factually accurate
  • Variations >70% structurally different
  • content-drafts.md updated successfully
  • No meta-commentary in output
  • Character limits respected
  • Hook-Content-CTA structure followed

Example Output

✅ Draft Generation Complete

Theme: First Money From Code
Variations Generated: 5

1. Bold Statement (Contrast + Authority)
2. Story Hook (Curiosity + Liking)
3. Problem-Solution (Social Proof + Reciprocation)
4. Data-Driven (Authority + Reason-Respecting)
5. Emotional Lollapalooza (6 biases)

Output File: content-drafts.md

Next Step: Run /content-score-all to apply framework scoring

Error Handling

If theme not found:

  • List available themes from themes-memory.md
  • Ask user to specify correct theme name

If sub-agent fails:

  • Retry that specific sub-agent only
  • Don't re-run all 5

If variations too similar:

  • Regenerate similar variation with stronger bias differentiation

Next Steps

After successful generation:

  1. Review variations in content-drafts.md
  2. Run /content-score-all to apply automated scoring
  3. Or continue with full pipeline if running /content-full-pipeline