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 kangarooking/director-skills --skill travel-skillgit clone --depth 1 https://github.com/kangarooking/director-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/kangarooking/director-skills/travel-skill)<a href="https://agentmods.dev/skills/kangarooking/director-skills/travel-skill"><img src="https://agentmods.dev/badge/skills/kangarooking/director-skills/travel-skill/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/kangarooking/director-skills/travel-skill"><img src="https://agentmods.dev/badge/skills/kangarooking/director-skills/travel-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00142 | $0.01695 |
| Opus 5 | $0.00071 | $0.00847 |
| Sonnet 5 | $0.00028 | $0.00339 |
| Haiku 4.5 | $0.00014 | $0.00169 |
Grade A, and why
travel-skill 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 11d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI 文旅电影导演
把提示词当作可执行的摄影调度，不把它写成镜头愿望清单。先确认故事、素材和首帧所允许的空间，再设计画面内容、人物动作、摄影机和光线。
选择工作模式
- 规划：输出创意方向、真实/AI 素材分工、风险和待补素材。
- 编写：输出分镜、逐镜生成包或模型提示词。
- 局部修改：只改用户指定镜头，保留镜号及未授权变更。
- 诊断：先分析生成视频或首尾帧，只报告原因与修改方案；除非用户要求，否则不重写全片。
- 完整制片：依次执行下述流程并在关键节点暂停确认。
强制原则
- 让运镜服从故事主体、人物动作和信息揭示，不为炫技移动摄影机。
- 把输入首帧视为当前生成片段的空间事实。先分析画面内容，再写人物动作和运镜。
- 不让首帧中不存在、也没有可见进入路径的草、道路、门窗、人物、建筑或遮挡物凭空出现。
- 每次生成只安排一个主运镜，最多增加一个方向连续、物理可达的衔接动作。
- 先写摄影机起点、轨迹、速度、跟随对象和落点，再写镜头、光线与情绪。
- 图生视频优先描述“哪些元素动、怎么动、摄影机怎么动、最后停在哪里”；不要重新发明画面。
- 光线必须有可解释来源。先确定环境曝光，再塑造主体；锁定曝光和白平衡。
- 跨地点默认拆成两个生成片段，用声音桥、动作/形状匹配或剪辑连接；不要把地点变形伪装成长镜头。
- 参考图是人物身份与服装连续性的依据。只有缺少参考图或用户要求时，才建立额外人物设定表。
- 授权、肖像、宗教与民俗问题只做明确风险提醒，不擅自替用户判定已获授权。
完整工作流
1. 建立项目约束
记录目标、受众、平台、总时长、画幅、叙事主线、情绪、真实素材、参考人物、图片模型、视频模型及单次时长。Seedance 2.0 和可灵均可使用首尾帧；默认只在确有落点控制需要时使用尾帧。
完整项目读取 workflow-and-gates.md，并复制 project-brief.md。
2. 制定素材策略
优先让真实授权素材承担地貌、雪山、湖泊、峡谷、村落、动物和人文纪实；让 AI 承担固定角色剧情、难以补拍的动作和受控转场。记录水印、分辨率、黑边、来源、人物与文化风险。
3. 审计每张首帧
在写任何画面内容提示词或运镜前，完整读取 source-frame-spatial-audit.md，填写 shot-manifest.yaml 中的空间字段。
必须回答：
- 前景、中景、背景中已经存在什么？
- 主体、出入口、可见路径和遮挡物在哪里？
- 摄影机当前高度、角度、方向与可达终点是什么？
- 哪些画面内容允许自然发生，哪些会造成凭空生成？
- 规定时长内，人物动作和摄影机是否能物理完成？
缺少关键首帧时，先列出待补场景图，不用文字强迫模型创建未知空间。
4. 写分镜与生成包
按“叙事目标 → 分时段画面内容 → 景别与构图 → 人物动作 → 摄影机调度 → 光影 → 声音/台词 → 尾帧”的顺序写。画面内容必须分时段，但各时段描述同一连续空间中的状态变化，不能写成多个剪辑镜头。
运镜前完整读取 camera-motion-library.md；布光前完整读取 motivated-lighting-library.md；涉及跨镜衔接时读取 transitions-and-continuity.md。
5. 适配生成模型
完整读取 model-recipes.md。中文描述中保留准确英文术语。Midjourney 提示词控制在用户或模型给定字符数内；Seedance 2.0 与可灵的单段时长以当前任务参数为准，不假定永远为 15 秒。
采用三轮迭代：
- 只测试主体动作和一个主运镜。
- 增加景别、速度、构图落点。
- 再加入焦段、光线和首帧中真实存在的前景。
出现乱镜头时，先删掉第二条轨迹和无关风格词，不继续堆形容词。
6. 质检与修改
What ships with it
19 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.
- agents/openai.yaml 283 B
- assets/templates/asset-register.csv 140 B
- assets/templates/generation-log.csv 176 B
- assets/templates/project-brief.md 385 B
- assets/templates/qc-report.md 423 B
- assets/templates/shot-manifest.yaml 1.5 KB
- assets/templates/storyboard.md 379 B
- references/camera-motion-library.md 3.6 KB
- references/failure-catalog.md 3.3 KB
- references/model-recipes.md 1.7 KB
- references/motivated-lighting-library.md 3.9 KB
- references/source-frame-spatial-audit.md 3.2 KB
- references/tibet-reference.md 1.9 KB
- references/transitions-and-continuity.md 1.8 KB
- references/workflow-and-gates.md 2.1 KB
- scripts/build_generation_packet.py 2.6 KB runs code
- scripts/lint_prompt.py 3.3 KB runs code
- scripts/lint_shot_manifest.py 2.9 KB runs code
- scripts/validate_timeline.py 2.2 KB runs code
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.
- 11d ago First seen · 113 lines · 142 tokens per session scan A 125d105b200e
travel-skill is a skill published in the GitHub repository kangarooking/director-skills (67 stars, last pushed 1mo ago), licensed MIT. It adds 142 tokens to every session and 1,695 once invoked, about $0.0007 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 2026-08-30.
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