Short Drama Hit Previewer

Problem It Solves

Short-drama scripts are hard to judge from intuition alone. Early hooks, ending tension, comment reactions, and platform packaging all affect retention, but creators often lack a repeatable way to test a script before production. This skill turns a script into scored dimensions and simulated audience signals, making it easier to compare versions, prepare launch plans, and design A/B tests.

How It Works

• First-10-second hook analysis: scores visual impact, conflict clarity, emotional tension, and memorable details, then offers optimization notes.
• Ending suspense analysis: evaluates suspense strength, willingness to continue, emotional afterglow, and visual metaphor for multi-episode scripts.
• Viral potential prediction: produces an overall score and estimates early retention, completion rate, sharing rate, and comment density.
• Comment reaction simulation: generates platform-style comments and breaks down praise, jokes, questions, and complaints into an emotional heat map.
• Platform adaptation: suggests title wording, tags, publishing time, interaction design, and visual style.
• Runtime setup: runs as a prebuilt bundle with a Node.js 22 runtime; optionally reads ~/.openclaw/openclaw.json to use the current OpenClaw model, and falls back to local heuristics when AI is unavailable.

Boundaries

The output is a prediction from script text and simulated signals, not a guarantee of performance. It does not replace acting, editing, casting, or production quality. Use it for script review, version comparison, A/B testing, and platform strategy, then validate with small-scale tests before full release.