drama-analyzer

drama-analyzer is a skill for Claude Code from GongLingRui/screen-creative-skills. It costs 47 tokens per session (1,209 once invoked), scanned A, a copy of drama-evaluator, MIT.

A tool that reads a novel, screenplay outline, or story summary and identifies its main turning points and the dramatic role of each one.

In plain words
What is it for?
Use it to map key plot changes, study dramatic structure, evaluate story momentum, and prepare material for screenplay adaptation.
Why use it?
It makes the story’s structure, pacing, and emotional movement easier to understand without rewriting the events.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; mentions Claude Code.

Good fit Use it to map key plot changes, study dramatic structure, evaluate story momentum, and prepare material for screenplay adaptation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gonglingrui/screen-creative-skills/drama-analyzer
Install

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.

Any agent
npx skills add GongLingRui/screen-creative-skills --skill drama-analyzer
Clone the repo
git clone --depth 1 https://github.com/GongLingRui/screen-creative-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for drama-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/drama-analyzer/github.svg)](https://agentmods.dev/skills/gonglingrui/screen-creative-skills/drama-analyzer)
Your own site
<a href="https://agentmods.dev/skills/gonglingrui/screen-creative-skills/drama-analyzer"><img src="https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/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.

agentmods 80×15 button for drama-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/gonglingrui/screen-creative-skills/drama-analyzer"><img src="https://agentmods.dev/badge/skills/gonglingrui/screen-creative-skills/drama-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,209 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 89% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.01209
Opus 5 $0.00023 $0.00605
Sonnet 5 $0.00009 $0.00242
Haiku 4.5 $0.00005 $0.00121

Measured 12d ago against content hash b803b36d14a3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 12d 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.

Origin

This is a copy

89% identical to drama-evaluator — 140 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.

category/story-analysis/drama-analyzer/SKILL.md · 114 lines

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

  1. 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
  2. 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
  3. 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
  4. 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
Files

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.

Changes

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.

  1. 12d ago First seen · 114 lines · 47 tokens per session scan A b803b36d14a3

Subscribe to this mod's changes

drama-analyzer is a skill published in the GitHub repository GongLingRui/screen-creative-skills (400 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 1,209 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to drama-evaluator, differing in 140 lines, and is treated as a copy.

Related

Other skills, from other repositories

analyze-generative-diffusion-model

Analyze pre-trained generative diffusion models (Stable Diffusion, DALL-E, Flux) by computing quality metrics (FID, IS, CLIP score, precision/recall), inspecting noise schedules, extracting and visualizing attention maps, and probing latent spaces. Use when evaluating a pre-trained generative diffusion model's output…

pjt222/agent-almanac · 104 tokens

compose-sacred-music

Compose or analyze sacred music in Hildegard von Bingen's distinctive modal style. Covers modal selection, melodic contour (wide-range melodies), text-setting (syllabic and melismatic), neumatic notation, and liturgical context for antiphons, sequences, and responsories. Use when composing a new piece in Hildegardian…

pjt222/agent-almanac · 108 tokens

create-spatial-visualization

Create interactive maps, elevation profiles, and spatial visualizations from GPX tracks, waypoints, or route data using R (sf, leaflet, tmap) or Observable (D3, deck.gl). Covers data import, coordinate system handling, map styling, and export to HTML or image formats. Use when visualizing a planned or completed tour…

pjt222/agent-almanac · 111 tokens

create-2d-composition

Compose 2D graphics programmatically using SVG generation, diagram layout algorithms, image compositing, and batch processing workflows. Use when generating diagrams, flowcharts, or infographics programmatically, creating reproducible scientific figures, automating production of badges or visual assets, building…

pjt222/agent-almanac · 77 tokens

create-3d-scene

Set up a Blender scene programmatically via Python (bpy) with objects, materials, lighting, camera, and environment configuration. Use when creating reproducible 3D visualization scenes, automating product or architectural rendering setup, generating multiple scene variations programmatically, building template scenes…

pjt222/agent-almanac · 77 tokens

configure-putior-mcp

Configure the putior MCP server to expose 16 workflow visualization tools to AI assistants. Covers Claude Code and Claude Desktop setup, dependency installation (mcptools, ellmer), tool verification, and optional ACP server configuration for agent-to-agent communication. Use when enabling AI assistants to annotate and…

pjt222/agent-almanac · 92 tokens