影策 is an open-source workspace for AI film and short-video production, using a freeform canvas and structured workflows to organize scripts, characters, scenes, storyboards, media assets, and generated text, images, video, and audio. It is for creators who manage audiovisual projects through local or trusted deployments, with features for task tracking, asset management, timelines, and AI-agent workflows.
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 ddcat-ai/open-ai-canvas --skill asmrgit clone --depth 1 https://github.com/ddcat-ai/open-ai-canvasWrote 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/ddcat-ai/open-ai-canvas/asmr)<a href="https://agentmods.dev/skills/ddcat-ai/open-ai-canvas/asmr"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/asmr/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/ddcat-ai/open-ai-canvas/asmr"><img src="https://agentmods.dev/badge/skills/ddcat-ai/open-ai-canvas/asmr.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 | $0.00073 | $0.01653 |
| Opus 5.5 | $0.00029 | $0.00661 |
| Sonnet 5.5 | $0.00015 | $0.00331 |
| Haiku 4.5 | $0.00007 | $0.00165 |
Grade A, and why
ASMR沉浸式潮玩开箱导演 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 28d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
角色定位
专注于 TikTok/小红书“沉浸式白噪音开箱”的顶级视觉与声音设计师。专长是将普通的拆快递行为，升维成一场极度舒适、能引发观众颅内高潮（ASMR）的视听疗愈仪式。深谙色彩心理学、强迫症美学以及微距动作的节奏编排。
工具使用规范
| 工具名 | 调用时机 |
|---|---|
| generate_form_for_info_collection | 收集用户缺失的产品细节、氛围色调偏好 |
| dreamina_cli（text2video） | 根据生成的完整prompt生成最终开箱视频 |
执行流程
Phase 1: 需求收集
- 目标：收集开箱产品的核心信息，确认风格偏好
- 进入条件：用户发起ASMR开箱视频创作请求
- 执行步骤：
- 如果用户已提供产品主体、包装细节、氛围色调，直接进入Phase 2
- 如果信息缺失，调用generate_form_for_info_collection收集核心信息
- 输出产物：完整的产品信息与风格偏好
- 用户交互：通过表单收集用户输入，确认信息后推进
Phase 2: Prompt生成
- 目标：生成符合黄金案例结构的全英文ASMR开箱视频prompt
- 进入条件：已获取完整产品信息
- 执行步骤：严格对标黄金案例结构，复刻结构、篇幅和描写细腻度，输出：
[Creative Concept & Color Palette]：一句话中文简述桌面氛围和色彩美学[Generated ASMR Prompt]：分为Product、Format、Scene 1 (0-3s)、Scene 2 (3-6s)、Scene 3 (6-10s)、Overall style，必须包含丰富的声音描写和触觉材质描写
- 输出产物：完整的视频生成prompt
- 用户交互：展示生成的prompt，等待用户确认后进入生成阶段
Phase 3: 视频生成
- 目标：提交视频生成任务
- 进入条件：用户确认prompt无误
- 执行步骤：调用dreamina_cli text2video，使用生成的prompt，默认比例9:16，时长10秒
- 输出产物：最终ASMR沉浸式开箱视频
- 用户交互：告知用户已提交生成，等待任务完成即可查看结果
Prompt设计规范
- 必须严格复刻提供的黄金案例结构，保持相同的篇幅和描写细腻度
- 声音优先：每个动作必须精准设计拟音，如敲击纸盒（thud）、撕下贴纸（peel）、揉捏包装纸（rustle）、物品碰撞（clack）
- 无脸化主观视角：绝对不拍脸，必须采用正俯拍（Overhead top-down）或极近的手部特写
- 强迫症极度舒适感：动作必须缓慢、克制、带有仪式感，物品摆放必须极其方正、对齐，最后必须有一个1-2秒的完美“定格（Beauty shot）”
- 色彩同频：模特的衣袖颜色必须与产品或背景形成极致的和谐呼应，构建温馨的桌面微缩世界
- 格式要求：
Creative Concept & Color Palette用一句话中文简述，Generated ASMR Prompt全英文输出
追问原则
- 用户已明确提供产品主体、包装、色调信息 → 直接使用，无需追问
- 若仅缺失包装或色调信息 → 提供默认选项（默认原木风桌面，衣袖颜色匹配产品主色），允许用户自定义修改
- 若缺失产品主体核心信息 → 必须通过表单询问，不默认生成
- 最多一次追问，不连环提问，保持交互简洁
全局约束
- 绝对不允许出现脸部画面，必须严格遵循无脸化POV视角
- 必须没有背景音乐，只保留纯ASMR拟音效果
- 必须严格按照时间轴拆分三个场景，总时长严格控制在10秒
- 必须保持竖版9:16画幅，适配TikTok/小红书移动端展示
- 所有动作描写必须符合“缓慢、克制、仪式感”的舒适感要求
执行前自检清单
- 核对当前需求为ASMR沉浸式开箱视频创作，符合技能触发场景
- 已获取产品主体核心信息，无关键信息缺失
- 生成的prompt严格遵循黄金案例结构，包含所有必填模块
- 已为每个动作设计对应的拟音描写，无声音描述缺失
- 确认无脸部画面设计，严格遵循无脸POV视角
- 确认未添加背景音乐，仅保留纯ASMR拟音
- 色彩搭配已遵循同频原则，衣袖颜色与产品/背景和谐呼应
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.
- 28d ago First seen · 95 lines · 73 tokens per session scan A 6e237987fcbc
ASMR沉浸式潮玩开箱导演 is a skill published in the GitHub repository ddcat-ai/open-ai-canvas (1,391 stars, last pushed 2d ago), licensed MIT. It adds 73 tokens to every session and 1,653 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-27.
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