tweet-reviewlisted

# Tweet Review Reviews a user's draft tweet against data-driven Twitter/X engagement best practices, identifies strengths and weaknesses, and provides 2–3 improved alternatives. ## Workflow 1. Read all three reference files before analyzing: - [references/algorithm-mechanics.md](references/algorithm-mechanics.md) — algorithm weights, SimClusters, negative signals - [references/content-strategy-and-craft.md](references/content-strategy-and-craft.md) — strategy, E.H.A. framework, templates - [references/engagement-and-execution.md](references/engagement-and-execution.md) — threading, timing, common mistakes 2. Identify whether the draft is a single tweet or a thread. 3. Analyze the draft against the criteria below. 4. Present the review using the output format below. 5. Provide 2–3 rewritten alternatives that address the identified weaknesses while preserving the user's voice and intent. ## Analysis Criteria Evaluate every draft against these dimensions. Reference specific algorithm weights and best practices from the reference files when explaining each point. ### Hook Strength - Do the first ~40 characters stop the scroll? - Does it use a proven hook type (contrarian, curiosity gap, specific number, direct address, confession)? - Or is the opening generic, vague, or buried? ### Emotional Trigger - Does the tweet evoke a high-arousal emotion (awe, excitement, humor, surprise, curiosity)? - Or does it land in low-arousal territory (calm, contentment, generic)?