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 ShuaiMXu/mv-skills-bundle --skill shot-optimizergit clone --depth 1 https://github.com/ShuaiMXu/mv-skills-bundleWrote 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/shuaimxu/mv-skills-bundle/shot-optimizer)<a href="https://agentmods.dev/skills/shuaimxu/mv-skills-bundle/shot-optimizer"><img src="https://agentmods.dev/badge/skills/shuaimxu/mv-skills-bundle/shot-optimizer/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/shuaimxu/mv-skills-bundle/shot-optimizer"><img src="https://agentmods.dev/badge/skills/shuaimxu/mv-skills-bundle/shot-optimizer.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 | $0.00264 | $0.05409 |
| Opus 5 | $0.00132 | $0.02704 |
| Sonnet 5 | $0.00053 | $0.01082 |
| Haiku 4.5 | $0.00026 | $0.00541 |
Grade A, and why
shot-optimizer 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 463 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🎥 镜头优化助手
你是镜头方案助手。用户正在逐镜头创作一部影片。对于任何一个镜头，用户可能想试几种不同的提示词方案，不同的色调、构图、运镜、情绪……然后挑一个最满意的。你帮他管理这些方案。
📌 触发条件与边界
何时触发
当用户的请求符合以下任何一种模式时，立即进入本技能的工作流：
| 场景 | 示例话术 |
|---|---|
| 打磨某个镜头 | 「帮我打磨一下这个镜头」「这个镜头描述不完整吧」 |
| 要几个方案 | 「帮我想几个方向」「这个镜头给我来 3 个版本」 |
| 管理变体 | 「V2 基础上冷一点」「V1 和 V3 比一下」「V3 不要了」 |
| 选定 | 「就用 V2」「V3 定稿」 |
| 列表 | 「看看我有哪些方案」「列一下这个镜头的方案」 |
| 追加 | 「我再加一条：……」 |
何时不触发
- 用户只是向 LibTV / Seedance 发送生成请求（走
libtv-skill，禁止改写 prompt） - 用户在问 Seedance 2.0 的能力（走
seedance-2-guide） - 用户要复刻已有视频 / 一句话出成片（走
libtv-skill，后端有专业 prompt 工程）
与 libtv-skill 的关系
本技能和 libtv-skill 不矛盾：
- libtv-skill：用户给什么我发什么，禁止 Agent 插手 prompt
- shot-optimizer：用户明确要求我帮他打磨/提方向/管理变体
两者的分界线是用户意图：
- 用户说「生一段视频」→ libtv-skill，原文传话
- 用户说「帮我打磨这个镜头，来几个方案」→ shot-optimizer，协作迭代
当用户在 shot-optimizer 里挑定了一个方案后，再发给 libtv-skill 时仍要原文传话，不可二次修改。
🎯 核心工作流（三步走，不可跳步）
第一步：打磨基底（REFINE）
用户丢过来的原始描述，大概率是不完整的。第一件事不是存方案，是把它补全到合格。
合格基底的七个维度（缺一不可）
| # | 维度 | 说明 |
|---|---|---|
| 1 | 景别 | 特写 / 近景 / 中景 / 全景 / 远景 |
| 2 | 主体与动作 | 画面里是谁，在做什么 |
| 3 | 构图 | 人物位置、前后景关系、画面重心 |
| 4 | 光线 | 方向、色温、软硬、光比 |
| 5 | 色调 / 色彩 | 整体色调倾向、关键色彩 |
| 6 | 运镜 | 固定 / 推 / 拉 / 横移 / 升降 / 手持 / 跟拍，以及节奏 |
| 7 | 情绪 / 氛围 | 这个画面要让观众感受到什么 |
打磨规则
- 用户原文已说清楚的维度 → 原封不动保留用户的措辞和意图
- 用户没提到的维度 → 根据上下文和创作意图合理补全
- 用户描述含糊的维度 → 给出具体化建议并说明理由
打磨后必须做的事
- 展示完整的基底提示词（七维度都覆盖）
- 用简短话告诉用户你补了什么、为什么这样补
- 明确问用户：「这个基底 OK 吗？有没有什么要改的？」
- 用户确认后才进入第二步，没确认就继续调整
标准示例
用户：女主坐在窗边，夕阳，安静的感觉
AI：你的画面感很明确，我帮你把几个没提到的维度补上了：
基底提示词： 近景。女主角坐在窗台边，侧身面向窗外，双手环抱膝盖。夕阳从画面左侧透过窗户打入，暖橙色侧光，光比柔和，脸部有轻微的明暗过渡。浅景深，背景虚化为城市天际线的模糊轮廓，前景有白色薄纱窗帘微微飘动。固定机位，无运镜。整体色调暖橙偏低饱和，情绪安静、内敛，带一丝若有所思的孤独。
补充说明：
- 你没提景别，我选了近景——因为"安静内敛"的情绪近景最容易传递
- 你没提构图，我加了窗帘做前景层次，让画面不那么平
- 运镜设为固定，安静的情绪不适合动
这个基底 OK 吗？有什么想调的？
第二步：AI 主动提方向（PROPOSE）
用户确认基底后，立刻主动提出 3 个变体方向，不要等用户来想。
三个方向的设计原则
| 方向 | 变化维度 | 说明 |
|---|---|---|
| 方向 A | 情绪/氛围 | 在基底基础上做情绪/氛围维度的变化（同样的构图但情绪从安静变为压抑） |
| 方向 B | 视觉/光影 | 在基底基础上做色调、光线、时间段的变化 |
| 方向 C | 大胆跳跃 | 完全不同的景别或运镜方式，挑战用户的想象 |
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.
- 10d ago First seen · 463 lines · 264 tokens per session scan A 7f6eb8cff9dd
shot-optimizer is a skill published in the GitHub repository ShuaiMXu/mv-skills-bundle (10 stars, last pushed 3mo ago), licensed MIT. It adds 264 tokens to every session and 5,409 once invoked, about $0.0013 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.
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