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 GongLingRui/screen-creative-skills --skill plot-points-analyzergit clone --depth 1 https://github.com/GongLingRui/screen-creative-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/gonglingrui/screen-creative-skills/plot-points-analyzer)<a href="https://agentmods.dev/skills/gonglingrui/screen-creative-skills/plot-points-analyzer"><img src="https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/plot-points-analyzer.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.01152 |
| Opus 5 | $0.00018 | $0.00576 |
| Sonnet 5 | $0.00007 | $0.00230 |
| Haiku 4.5 | $0.00004 | $0.00115 |
Grade A, and why
plot-points-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.
This is a copy
80% identical to drama-evaluator — 158 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
情节点分析专家
功能
分析故事中的情节点，识别关键情节与转折点，描述情节发展过程。
使用场景
- 深度分析故事情节结构，揭示内在逻辑。
- 识别故事的关键转折节点，评估其对剧情的影响。
- 评估情节发展的有效性与合理性。
- 为情节优化与剧本改编提供专业建议。
核心步骤
- 识别: 识别故事中的所有重要情节点。
- 重要性评估: 分析情节点的重要性级别（核心/重要/辅助）。
- 类型分类: 按情节功能对情节点进行类型分类（开端/发展/转折/高潮/结局）。
- 过程描述: 描述情节点发展的完整过程，包括前置条件、发展与结果。
- 转折分析: 分析情节转折点的性质、机制与对情绪的影响。
输入要求
- 故事文本或情节大纲: 完整的原始故事文本或详细的情节大纲。
- 特定分析重点（可选）: 指定需要重点分析的情节点或方面。
输出格式
【情节点 X】：情节点名称
1. 情节点类型
- 类型：[开端/发展/转折/高潮/结局]
- 功能：具体描述该情节点的功能
2. 情节点重要性
- 重要性级别：[核心/重要/辅助]
- 影响范围：描述对整体故事的影响
3. 情节发展过程
- 前置条件：什么条件导致了这个情节点
- 发展过程：情节是如何发展的
- 结果导向：产生了什么结果
4. 转折点分析
- 转折性质：[正面/负面/中性]
- 转折机制：转折是如何实现的
- 情绪影响：对观众情绪的影响
5. 情节对故事的影响
- 对角色发展的影响
- 对主线情节的推动作用
- 对主题表达的贡献
约束条件
- 分析结果需忠实于原始故事文本，不进行主观臆断。
- 确保情节点分类准确，功能描述清晰。
- 建议具备可操作性，能指导情节优化。
示例
参见 {baseDir}/references/examples.md 目录获取更多详细示例:
examples.md- 包含不同类型故事（如都市爱情、古装玄幻、悬疑推理）的关键情节点分析示例。
详细文档
参见 {baseDir}/references/examples.md 获取关于情节点分析的详细指导与案例。
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；添加 allowed-tools (Read) 和 model (opus) 字段；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 |
| 1.0.0 | 2026-01-10 | 初始版本 |
What ships with it
1 file 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 · 120 lines · 37 tokens per session scan A e6de772777c8
plot-points-analyzer is a skill published in the GitHub repository GongLingRui/screen-creative-skills (392 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to drama-evaluator, differing in 158 lines, and is treated as a copy.
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