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Tweet Optimization

Créé par Ask Mojo

Transforms draft tweets into algorithm-optimized versions for maximum engagement on X. Analyzes hooks, emotional resonance, reply triggers, and repost psychology. Use when drafting tweets, improving post performance, or asking for viral content optimization.

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Tweet Optimization

Transforms draft tweets into high-engagement versions optimized for X's algorithm.

Quick Start

  1. Provide your draft tweet or idea
  2. Receive analysis of current strengths and friction points
  3. Get 3 optimized versions (hook-focused, reply-maximizing, repost-optimizing)
  4. Choose recommended version or hybrid

How X's Algorithm Scores Tweets

The For You feed predicts engagement probabilities. Optimize for:

Positive signals (maximize):

  • Likes, replies, reposts, quotes
  • Clicks, dwell time, shares, follows

Negative signals (avoid):

  • Not interested, block, mute, report

Optimization Framework

1. Hook Engineering (First 7 Words)

  • Pattern interrupt: Break expectations
  • Curiosity gap: Open a loop that demands closing
  • Specificity: Concrete beats abstract ("$47M" not "millions")
  • Contradiction: Challenge assumed beliefs

2. Emotional Resonance

Target high-arousal emotions that drive action:

  • Awe ("this changes everything")
  • Anger (righteous, not toxic)
  • Anxiety (FOMO, urgency)
  • Surprise (unexpected reveals)
  • Validation ("finally someone said it")

Avoid low-arousal states: sadness, contentment, boredom.

3. Reply Maximization

Build in reply triggers:

  • Hot takes that demand response
  • Questions (real or rhetorical)
  • Intentional incompleteness ("but there's a catch...")
  • Rankings that people want to argue with
  • Polarizing framing on non-toxic topics

4. Repost Psychology

Make it identity-reinforcing:

  • "This is the kind of person I am"
  • Makes the sharer look smart/informed/funny
  • Tribal signaling without being exclusionary
  • Quotable standalone value

5. Dwell Time Optimization

  • Information density that rewards re-reading
  • Nested ideas that unfold
  • Formatting that guides the eye
  • Payoff that recontextualizes the hook

6. Negative Signal Avoidance

Never trigger:

  • Spam patterns (excessive hashtags, @mentions, links in first tweet)
  • Engagement bait that feels manipulative ("RETWEET IF...")
  • Rage bait that makes people want to mute
  • Cringe that embarrasses readers

Output Format

For each input tweet, provide:

ORIGINAL: [their tweet]

ANALYSIS:
- Current engagement drivers: [what works]
- Friction points: [what hurts it]
- Emotional register: [current vs optimal]
- Missing elements: [opportunities]

OPTIMIZED VERSION 1 (Hook-focused):
[rewrite]
Why it works: [explanation]

OPTIMIZED VERSION 2 (Reply-maximizing):
[rewrite]
Why it works: [explanation]

OPTIMIZED VERSION 3 (Repost-optimizing):
[rewrite]
Why it works: [explanation]

RECOMMENDED: [which version + hybrid suggestions]

POSTING STRATEGY:
- Best time framing: [if relevant]
- Thread potential: [yes/no + why]
- Media recommendation: [image/video/none + why]
- Follow-up plays: [what to do after posting]

Style Guidelines

  • Write like a human, not a marketer
  • Lowercase is fine if it fits the voice
  • Short sentences. Punchy.
  • No cringe corporate-speak
  • Match the author's authentic voice while amplifying it
  • Weird beats boring. Specific beats generic. Confident beats hedging.

Example

Input: "We just launched our new product after 6 months of work"

Analysis:

  • Current drivers: Milestone announcement, effort narrative
  • Friction: Generic, no hook, passive voice
  • Emotional register: Low (contentment) vs optimal (surprise/awe)
  • Missing: Tension, specificity, curiosity gap

Optimized Version 1 (Hook-focused):

6 months ago we mass-deleted our codebase.

today we shipped the thing that almost killed us.

Why: Opens with unexpected action (pattern interrupt), creates narrative tension, "mass-" repetition creates rhythm.

Optimized Version 2 (Reply-maximizing):

we mass-resigned the team, mass-deleted the code, and mass-rebuilt from zero.

6 months later: we just shipped.

was it worth it? (thread below)

Why: Creates controversy ("mass-resigned?"), promises story, invites debate.

Optimized Version 3 (Repost-optimizing):

the product that almost killed us just shipped.

6 months of mass-deletes, mass-resignations, and mass-rebuilds.

here's the lesson nobody tells you about startup launches:

Why: Shareable insight framing, makes reposter look wise, promises valuable lesson.

Recommended: Version 1 for clean impact, or Version 3 if you have a thread ready.

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