zenstory-ai/drama-skills is a collection of AI coding-agent skills for producing short dramas and animated stories from an idea or source material, covering scripts, visual assets, storyboards, and image, video, and audio prompts. It is intended for screenwriters, animation studios, and directors using Claude Code, Codex, or other agents that support the Agent Skill format. The catalogue skills are the project's own workflow for planning, reviewing, and producing these projects.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zenstory-ai/drama-skills --skill short-drama-reviewgit clone --depth 1 https://github.com/zenstory-ai/drama-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zenstory-ai/drama-skills/short-drama-review)<a href="https://agentmods.dev/skills/zenstory-ai/drama-skills/short-drama-review"><img src="https://agentmods.dev/badge/skills/zenstory-ai/drama-skills/short-drama-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zenstory-ai/drama-skills/short-drama-review"><img src="https://agentmods.dev/badge/skills/zenstory-ai/drama-skills/short-drama-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.01419 |
| Opus 5 | $0.00053 | $0.00709 |
| Sonnet 5 | $0.00021 | $0.00284 |
| Haiku 4.5 | $0.00011 | $0.00142 |
Grade A, and why
short-drama-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- short-drama-review — 100% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
短剧审查
优先由未参与当前版本创作的 reviewer 执行；条件不允许时可以自检并如实说明。审查与修改是两个工作 单元：本技能只定位问题、影响和必须达到的修订结果，不在同一轮替 owner 改来源。
Quick Start
直接读取用户点名的当前文件。单集审查需要落盘时写 审查/EP001-审查.md；独立文件审查使用
审查/<主题>-审查.md。用户只要口头结论时直接回复，不为“完整”创建审查文件。
审查 Markdown 建议结构：
# EP001 审查
- 范围：剧本、分镜、视频提示词
- 结论：REVISE
- 复核方式：独立 reviewer / 自检
## Blocker · REV-001 · 画面文字未被镜头承载
- 位置：剧本.md / EP001-SC002；分镜.md / SHOT-EP001-004
- 证据：……
- 影响：……
- 修订结果：由 short-drama-storyboard 补入准确文字及可读条件。
- 规则：SHT-01 · reviewed_invariant
引用只使用文件名、标题 ID、行号或短引文；不建立 sources 声明、哈希、record ID 或第二套状态。
选择审查范围
source_analysisstory_scriptassets_continuityimage_promptsstoryboard_keyframesvideo_promptsproduction_outputsfull_episodedelivery_privacyproject_calibration
只读对应资料，不预加载整个项目：
- 原著分析：原著分析审查表
- 故事、场景、行动与对白：故事剧本审查表
- 身份、变体、连续性与图片提示词：资产提示词审查表
- 原文落实、镜头、关键帧与视频运动：视觉运动审查表
- 完整审查方法：审查方法
- 制作端常见缺陷：生产质量门
- 授权生产观察的项目内校准：项目校准
- 模板感、重复手法或 AI 味：反模板修订
- 阶段边界、参考媒体与规则表：阶段契约
工作流
1. 冻结范围
写清当前要审哪些文件、章节、镜头或提示词，以及创作者已经明确的限制。目标在审查中发生变化时， 重新读取再下结论。
2. 先查可证明事实
- 五文档的可见 ID、引用和时长是否一致；
- 剧本对白、动作、声音、画面文字是否都有画面/声音承载；
- 人物、地点、道具状态和镜头起止是否连续；
- 提示词是否从准确起点到准确终点；
- 目标模型画音同轨时，声音内容、时序和发声边界是否与来源一致；无对白镜是否交代底声或静默
（
VID-22、VID-23，见 视觉运动审查表）； - 私有输入、凭据、绝对路径或内部流程文字是否泄漏。
缺少必要输入时只停止依赖它的判断，其他问题可以继续汇总。
3. 带证据审内容
每个 finding 包含：位置、必要短引文或冲突事实、观众/制作影响、必须达到的修订结果、owner、严重 程度和规则等级。不能只说“AI 味”“不够电影感”或给无证据分数。
4. 跨文档综合
剧本事实 -> 视觉设定 -> 镜头职责与边界 -> 冻结关键帧 -> 视频运动 -> 下一状态
优先守住原意、知情时机与连续性，不奖励脱离来源的华丽提示词。
5. 结论与分派
APPROVE：没有阻断问题；APPROVE_WITH_NOTES：只有不阻断的改进；REVISE：存在结构、内容或限制冲突；PROVISIONAL：关键输入不足，暂时无法完成判断。
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 252 B
- assets/finding-template.jsonl 1.2 KB
- assets/supersession-decision.example.json 1.2 KB
- assets/verdict-template.json 685 B
- examples/minimal-findings.jsonl 1.1 KB
- examples/minimal-verdict.json 674 B
- references/anti-template-repair.md 5.3 KB
- references/production-quality-gates.md 19 KB
- references/project-calibration.md 5.8 KB
- references/review-method.md 3.9 KB
- references/rubric-assets-prompts.md 5.4 KB
- references/rubric-source-analysis.md 5.4 KB
- references/rubric-story-script.md 16 KB
- references/rubric-visual-motion.md 10 KB
- references/stage-contract.md 3.1 KB
- scripts/review_check.py 12 KB runs code
- scripts/selftest.py 3.1 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · -1 lines 251364f35886
- 2d ago Changed · +3 lines 174bd5b69576
- 13d ago First seen · 117 lines · 107 tokens per session scan A 594a11ecb99c
short-drama-review is a skill published in the GitHub repository zenstory-ai/drama-skills (1,798 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 1,419 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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