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- shortdrama topic script
shortdrama topic script
Automated pre-production for short drama series: from scam mechanism auditing to timed, production-ready scripts.
$9
Works with the AI Agents you already use
shortdrama topic script
Example session with this skill installed
I have a new idea: a fake home appliance repair scam targeting the elderly. Verify if this works for the Uncle Zhao series and give me a scored proposal.
- Read your context and instructions
- Compiled the shortdrama topic script
Verified the "Fake Appliance Repair" mechanism against references/topic-bank.md. No direct collisions found. While "Free Health Checks" was used in Ep 4, the "Home Entry" trust structure is a fresh mechanism for this series.
Initial Topic Evaluation: Home Repair Trap
| Metric | Score | Weight | Weighted Score |
|---|---|---|---|
| Hook | 8/10 | 25% | 2.0 |
| Differentiation | 7/10 | 20% | 1.4 |
| Feasibility | 9/10 | 20% | 1.8 |
| Timeliness | 8/10 | 20% | 1.6 |
| Emotion | 7/10 | 15% | 1.05 |
| Total | 100% | 7.85 |
One-Sentence Hook: "Uncle Zhao, your fridge isn't broken, but your motherboard just 'blew up' the moment I touched it."
8-Scene Skeleton:
- Hook: Technician sparks a fake short circuit; Zhao panics.
- The Lure: Technical jargon about "imported components" and "urgent fire risk."
- The Trap: Low call-out fee vs. 2000 per cent "core replacement" cost.
- The Pressure: Technician offers a "neighbor discount" if paid in cash now.
- The Hesitation: Zhao calls Qiang to borrow money.
- The Clue: Qiang notices the "new" part has a 2019 dust layer.
- The Reversal: Zhao pretends to call the "Police Repair Hotline" for a second opinion.
- Ending: Technician flees; subtitle warns about unverified 400 numbers.
Next steps
- Run
scripts/score_topics.pywith fullcandidates.jsonto confirm rank. - Initialize folder
014.ApplianceScam/and copyassets/剧本模板.md. - Draft dialogue for Scene 3 focusing on Old Qian's "cost-logic" argument.
Connects securely to your tools. The creator never sees your data.
About this skill
Stop wasting time on redundant storylines and bloated short drama scripts that fail to engage. This skill automates the end-to-end development of serialized anti-fraud and consumer-trap short films, ensuring every episode fits your production constraints and hits high-retention metrics.
What it does
- Mechanism audit: Checks new ideas against a database of past episodes to prevent repetitive tropes and "re-skinned" plots.
- Weighted scoring: Evaluates topics using a five-dimension system (Hook, Differentiation, Feasibility, Timeliness, Emotion) with strict rejection criteria.
- Script generation: Converts outlines into production-ready scripts with clear action lines, dialogue blocks, and mid-scene beats.
- Duration estimation: Calculates word-count-to-second ratios to ensure episodes stay within the 80 to 100-second target range.
- Asset breakdown: Generates dialogue ledgers and clip-segmentation tables for rapid voiceover and filming.
How it works
- Series sync: Analyze your existing
series-canon.mdto load character arcs and previously used fraud mechanisms. - Topic filtration: Run
scripts/score_topics.pyon candidate ideas to identify high-potential hooks with low production overhead. - Structure expansion: Use the 8-scene framework to build a script skeleton including the "3-second hook" and the "reversal" ending.
- Validation: Execute
scripts/estimate_duration.pyto identify pacing bottlenecks and trim dialogue for fast-paced platforms.
Frameworks & tools
This tool uses custom Python scripts (score_topics.py, estimate_duration.py) and structured Markdown templates for consistent production output. It integrates with existing AI film pipelines by focusing on pre-production logic.
Why this beats prompting it yourself
Generic prompts often generate generic, repetitive "cautionary tales" that lack variable narrative structure. This skill enforces strict "one-out, one-in" character logic and mechanism-based differentiation that a standard LLM will ignore in favor of creative fluff.
Use cases
- Generating the next episode of an existing anti-fraud series like "Uncle Zhao."
- Fact-checking a real-world scam against production budgets to see if it can be filmed.
- Refactoring loose script drafts into tight, timed dialogues for voice actors.
- Maintaining a long-term "topic bank" for a content team to prevent creative burnout.
Known limitations
Does not generate H3 prompts, storyboards, or visual assets. Limited to short-form vertical video structures under 110 seconds. Requires an initial series canon file to avoid duplicates.
No support for H3 prompts or storyboard generation. Strictly for vertical short-form scripts under 110 seconds. Requires pre-existing series canon file for mechanism deduplication.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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- Software
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