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 agentmods add commands/js-mark/skills/dramagit clone --depth 1 https://github.com/JS-mark/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/commands/js-mark/skills/drama)<a href="https://agentmods.dev/commands/js-mark/skills/drama"><img src="https://agentmods.dev/badge/commands/js-mark/skills/drama.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 | $0.00012 | $0.00891 |
| Opus 5 | $0.00006 | $0.00445 |
| Sonnet 5 | $0.00002 | $0.00178 |
| Haiku 4.5 | $0.00001 | $0.00089 |
Grade A, and why
drama 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 3d 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
执行步骤
步骤一:确定路径 + 加载存档
- 如果用户在
/drama后指定了路径(如/drama ~/my-project),使用该路径作为<DRAMA_ROOT> - 如果之前的对话中已经确定过路径,沿用该路径
- 否则使用默认路径
~/Desktop/drama/
确定路径后:
- 使用 Glob 检查
<DRAMA_ROOT>/project.md是否存在 - 如果存在,依次 Read 以下文件恢复上下文:
<DRAMA_ROOT>/project.md— 项目配置<DRAMA_ROOT>/outline.md— 故事大纲<DRAMA_ROOT>/characters.md— 角色档案<DRAMA_ROOT>/progress.md— 创作进度
- 使用 Glob
<DRAMA_ROOT>/episodes/EP*.md查找已有剧本,Read 最近1-2集恢复剧情上下文
汇报当前状态:
📺 项目:《剧名》
📱 平台:竖屏短剧 / 横屏微短剧
🎭 题材:XX类型
📊 进度:已完成 XX/XX 集
🪝 上集钩子:[上一集结尾悬念]
➡️ 下集预告:[下一集核心冲突]
步骤二:判断当前阶段并执行
根据已有文件判断应进入哪个阶段:
情况 A: 无 project.md → 全新项目
- 进入「阶段一:项目设置」
- 使用 AskUserQuestion 引导用户选择平台类型、题材、集数等
- 完成后自动进入「阶段二:故事大纲」
情况 B: 有 project.md,无 outline.md → 需要写大纲
- 进入「阶段二:故事大纲」
- 参照
references/outline-template.md模板 - 参照
references/genre-templates.md中对应类型的结构
情况 C: 有 outline.md,无 characters.md → 需要设计角色
- 进入「阶段三:角色设计」
- 参照
references/character-template.md模板
情况 D: 有 characters.md,outline.md 中无分集大纲 → 需要写分集大纲
- 进入「阶段四:分集大纲」
- 为每集规划核心冲突和结尾钩子
情况 E: 分集大纲已有,可以写剧本 → 剧本创作
- 进入「阶段五:剧本创作」
- 从 progress.md 确定下一集集号
- 按分集大纲写下一集
步骤三:创作输出
无论处于哪个阶段,完成创作后:
-
保存文件 — 保存到对应路径:
- 大纲 →
<DRAMA_ROOT>/outline.md - 角色 →
<DRAMA_ROOT>/characters.md - 剧本 →
<DRAMA_ROOT>/episodes/EPXXX-标题.md - 分镜 →
<DRAMA_ROOT>/storyboard/EPXXX-分镜.md
- 大纲 →
-
更新进度 — 更新
<DRAMA_ROOT>/progress.md:- 记录完成状态
- 更新伏笔跟踪
- 标注大纲偏离(如有)
- 写下集预告
-
汇报结果 — 附上创作报告:
✅ 已完成:EPXXX《标题》 📊 台词字数:XXXX字 🎬 场景数:X场 🪝 本集钩子:[结尾悬念] ➡️ 下集预告:[下集核心冲突]
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.
- 3d ago First seen · 90 lines · 12 tokens per session scan A 0ed41227b275
drama is a command published in the GitHub repository JS-mark/skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 891 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.