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 yutianxiao6/openreel-studio --skill video-productiongit clone --depth 1 https://github.com/yutianxiao6/openreel-studioWrote 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/yutianxiao6/openreel-studio/video-production)<a href="https://agentmods.dev/skills/yutianxiao6/openreel-studio/video-production"><img src="https://agentmods.dev/badge/skills/yutianxiao6/openreel-studio/video-production/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/yutianxiao6/openreel-studio/video-production"><img src="https://agentmods.dev/badge/skills/yutianxiao6/openreel-studio/video-production.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 | $0.00079 | $0.02542 |
| Opus 5 | $0.00039 | $0.01271 |
| Sonnet 5 | $0.00016 | $0.00508 |
| Haiku 4.5 | $0.00008 | $0.00254 |
Grade A, and why
video-production 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
视频制作入口指南
模型摘要
video-production由自动 Skill 目录匹配,通过skills.list/skills.read读取;它不是 workflow 模板或 spec 来源,只提供视频制作入口规则和模块 Skill 索引。- 普通“制作视频/短剧/文生视频”默认使用模板
general_short_drama_workflow(显示名“通用视频制作工作流”),通过tool.search、tool.describe和tool.execute调用 deferredworkflow.run_step、workflow.run_next或workflow.run_all。 - 工作流请求通过
workflow_spec选择器返回现有模板引用;默认路径返回general_short_drama_workflow,不重新生成 spec。 - 默认视频运行模式只使用现有模板引用、补齐输入并运行 workflow。
- 用户主动要求查询或选择模板时,优先委派
workflow_spec选择器;只在需要展示列表时读取 workflow 模板目录。 - 运行前补齐阻塞输入:剧情/主题
plot、单集总时长duration_seconds;可选输入是视觉风格style、视频类型video_type、画面制作模式visual_plan_mode、集数episode_count和每段时长segment_seconds。visual_plan_mode默认storyboard,用户可在前端改为story_template。 - workflow spec 保持可移植,只描述结构、提示词、依赖和业务字段。模型、画幅、清晰度、画质等媒体产物参数由前端运行配置提供;总时长和分段时长必须连续核算,末段终点精确等于
duration_seconds。 - 模板里的 V2 逻辑步骤已经带
prompt;运行期编译成私有提示词阶段执行,不把完整 prompt skill 原文塞进主 Agent。 - prompt 模块索引用于模板维护、局部改提示词或 standalone 节点:剧本
script-writing,人物图character-prompt,场景图scene-prompt,宫格分镜shot-grid-prompt,视频提示词video-prompt,故事模板图story-template-method。 - 每个节点都是独立任务单元;
task只记录进度;生产依赖写节点fields.references,图片引用用role:"visual_reference",文字上下文用role:"context",直接采用已有图片用role:"source_image"。 - 最终 image/video prompt 提到参考图时,在每个对应语句中使用候选表给出的精确
@参考图标签,标签沿用完整画布标题并保留其中的|、|、空格、书名号等字符,例如“人物沿用@《回头》主角|15岁少年,镜头沿用@宫格分镜图”。后端先把标签绑定到稳定的图片节点 ID,画布和数据库保留可读标签;节点运行时,再按实际媒体提交顺序把所有绑定位置临时替换为图片1、图片2,不在提示词开头追加映射表。 fields.director_capture=true的图片是导演台构图参考,只继承人物/物体站位、朝向、姿态、比例、遮挡、景别和机位;正式分镜同时引用人物图与场景图重绘,不保留白模、色块、网格或编辑器外观,也不把构图参考自动当作视频首帧。- 当前轮通过
$video-production或带精确 path 的结构化 Skill 引用显式选择时,正文会在模型调用前以<skill>块注入;否则先用skills.list(authority={"kind":"orchestrator"})获取精确 handle,再用skills.read读取main_resource,沿next_cursor到 EOF。引用资源继续使用同一 authority/package;skill://是 source locator,不是文件路径。 - 只有用户要求诊断 UMA 视频调用、协议、target 或恢复行为时,再读取
references/video-model-calling.md。
默认模板
默认模板:
template_id: general_short_drama_workflow
name: 通用视频制作工作流
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.
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.
- 12d ago First seen · 136 lines · 79 tokens per session scan A 828e3f38142f
video-production is a skill published in the GitHub repository yutianxiao6/openreel-studio (29 stars, last pushed 26d ago), licensed MIT. It adds 79 tokens to every session and 2,542 once invoked, about $0.0004 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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