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 sutchan/Agent-Skills-Hub --skill drama-analyzergit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote 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/sutchan/agent-skills-hub/drama-analyzer)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/drama-analyzer"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/drama-analyzer/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/sutchan/agent-skills-hub/drama-analyzer"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/drama-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00048 | $0.01274 |
| Opus 5 | $0.00024 | $0.00637 |
| Sonnet 5 | $0.00010 | $0.00255 |
| Haiku 4.5 | $0.00005 | $0.00127 |
Grade A, and why
drama-analyzer 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 8d ago.
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.
What it actually says
剧本分析专家
功能
分析故事文本，提炼主要情节点并分析每个情节点的戏剧功能。基于资深编剧的专业视角，深入理解故事结构和戏剧张力。
使用场景
- 分析小说或故事文本的核心情节结构，梳理故事脉络
- 识别故事中的关键转折点和情感节点，理解故事节奏
- 评估每个情节点的戏剧作用和推动力，为改编提供依据
- 为剧本改编提供情节分析基础，确保改编质量
- 学习优秀作品的戏剧结构和情节设计技巧
核心步骤
- 深度阅读: 充分阅读和理解故事文本内容，把握整体结构和主题
- 情节点识别: 根据情节点定义，识别并总结故事中的主要情节点
- 戏剧功能分析: 深入分析每个情节点在故事中的戏剧作用、推动力和情感影响
- 结构化输出: 按照指定格式输出分析结果，确保清晰准确
输入要求
- 完整的故事文本（小说、剧本大纲、故事梗概等）
- 文本长度建议：500字以上
输出格式
【情节点】：<单个情节点描述>
【戏剧功能】：<该情节点的戏剧功能分析>
【情节点】：<单个情节点描述>
【戏剧功能】：<该情节点的戏剧功能分析>
...
要求
- 每个情节点的表述不超过100字
- 至少提炼5个情节点
- 严格按照故事文本原文意思总结，不自行创作改编
- 不使用阿拉伯数字为情节点标号
最佳实践
- 文本选择: 建议使用完整的故事文本，至少500字以上，确保有足够的情节内容
- 分析深度: 深入理解故事文本，不要停留在表面，要挖掘情节点的深层戏剧功能
- 客观准确: 严格按照故事文本原文意思总结，避免自行创作或添加不存在的情节
- 格式规范: 严格按照输出格式，每个情节点单独成段，清晰标注戏剧功能
详细文档
参见 {baseDir}/references/ 目录获取更多文档:
examples.md- 更多场景示例（悬疑、爱情、职场逆袭、古装宫斗、重生复仇等）guide.md- 完整分析指南，包含情节点定义和戏剧功能说明
版本历史
| 版本 | 日期 | 变更 |
|---|---|---|
| 2.1.0 | 2026-01-11 | 优化 description 字段，使其更精简并符合命令式语言规范；模型更改为 opus；优化功能、使用场景、核心步骤、输入要求、输出格式的描述，使其更符合命令式语言规范；添加约束条件、示例和详细文档部分。 |
| 2.0.0 | 2026-01-11 | 按官方规范重构，添加 references 结构 |
| 1.1.0 | 2026-01-10 | 添加多场景示例 |
| 1.0.0 | 2026-01-10 | 初始版本 |
What ships with it
2 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.
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.
- 8d ago First seen · 119 lines · 48 tokens per session scan A 857e196c3a10
drama-analyzer is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 1,274 once invoked, about $0.0002 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 2026-09-04.
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