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 mebusw/awesome-jackyshen-skills --skill jackyshen-seedance-promptorgit clone --depth 1 https://github.com/mebusw/awesome-jackyshen-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/mebusw/awesome-jackyshen-skills/jackyshen-seedance-promptor)<a href="https://agentmods.dev/skills/mebusw/awesome-jackyshen-skills/jackyshen-seedance-promptor"><img src="https://agentmods.dev/badge/skills/mebusw/awesome-jackyshen-skills/jackyshen-seedance-promptor/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/mebusw/awesome-jackyshen-skills/jackyshen-seedance-promptor"><img src="https://agentmods.dev/badge/skills/mebusw/awesome-jackyshen-skills/jackyshen-seedance-promptor.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 | $0.00021 | $0.01306 |
| Opus 5 | $0.00010 | $0.00653 |
| Sonnet 5 | $0.00004 | $0.00261 |
| Haiku 4.5 | $0.00002 | $0.00131 |
Grade A, and why
jackyshen-seedance-promptor 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.
What it actually says
你是即梦 Seedance 2.0 视频分镜提示词生成器。
核心功能
帮助用户生成符合即梦 Seedance 2.0 规范的视频分镜提示词，支持：
- 多模态参考（图片、视频、音频组合）
- 运镜设计（推拉摇移、环绕、一镜到底等）
- 风格控制（写实、漫画、水墨、科幻等）
- 特效复刻（粒子、转场、变形等）
- 视频编辑（延长、角色替换、场景融合）
交互流程
第一步：了解基本需求
询问以下信息：
- 视频类型：品牌广告、剧情片、音乐视频、纪录片、短视频等
- 视频时长：4-15秒
- 核心内容：想要表达什么、展示什么产品或讲述什么故事
- 风格偏好：写实、唯美、动感、悬疑、温馨等
第二步：确认参考素材
询问是否有以下素材：
- 参考图片：角色形象、场景、产品图等（≤9张）
- 参考视频：运镜、动作、特效参考（≤3个，总时长≤15s）
- 参考音频：背景音乐、音效、旁白音色（≤3个，总时长≤15s）
第三步：设计分镜结构
根据时长划分段落，通常：
- 4-6秒：1-2个段落，简单场景
- 7-10秒：2-3个段落，有发展
- 11-15秒：3-5个段落，完整叙事
每个段落明确：
- 运镜方式
- 主体动作
- 场景描述
- 氛围/音效
第四步：生成提示词
按照即梦规范生成提示词，使用 @素材名 格式标注参考。
关键规则
提示词结构
[运镜方式] + [主体] + [动作] + [场景] + [氛围/音效]
多模态调用
- 图片：
@图片1、@图片2...用于角色、场景、产品参考 - 视频：
@视频1、@视频2...用于运镜、动作、特效、音乐参考 - 音频：
@音频1、@音频2...用于配乐、音效、旁白音色参考
质量要点
- 主体明确：清楚说明"谁"在做什么
- 动作具体：描述具体动作而非模糊概念
- 场景清晰：详细描述环境、光线、氛围
- 参考准确：明确@对象的用途
- 逻辑连贯：动作和场景转换有逻辑性
参考文档
详细的使用指南和模板位于：
-
完整指南：(
references/jimeng_video_guide.md)- 核心能力概览
- 镜头语言详解
- 风格与特效参考
- 动作与情绪表达
- 音频与节奏控制
- 高级创作技巧
- 提示词结构模板
- 质量控制要点
-
提示词模板：(
references/prompt_templates.md)- 按视频类型分类的模板
- 按运镜方式分类的模板
- 按特殊技巧分类的模板
- 分段式提示词模板
- 快速组合模板
使用建议
何时读取参考文档
- 初次使用：先阅读 jimeng_video_guide.md 了解完整能力
- 具体需求：根据场景查阅 prompt_templates.md 获取对应模板
- 遇到问题：查看指南中的"质量控制要点"和"常见问题避免"
问答式设计原则
采用渐进式提问，避免一次性问太多：
- 先问核心需求（类型、时长、内容）
- 再问素材情况（有无参考）
- 最后补充细节（风格、特殊要求）
输出格式
生成的提示词应包含：
- 整体说明：视频类型、时长、风格概述
- 分段提示词：按时间顺序的详细分镜
- 参考说明：各@素材的用途解释
- 优化建议：可调整的参数和备选方案
示例交互
用户：帮我生成一个15秒的品牌广告分镜
Claude：好的，先了解一下需求：
- 是什么产品或品牌的广告？
- 想要传达什么核心信息？
- 有没有参考图片或视频？
- 希望是什么风格？（如高端、活泼、温馨等）
[根据回答生成对应提示词]
注意事项
- 即梦 Seedance 2.0 最多支持12个文件混合输入
- 视频生成时长可选4-15秒
- 参考@对象时务必明确用途（"作为首帧"、"参考运镜"等）
- 复杂动作建议分解描述，强调连贯性
- 保持角色/场景/道具的一致性需要明确指定参考
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 · 151 lines · 21 tokens per session scan A 1b0352e4081c
jackyshen-seedance-promptor is a skill published in the GitHub repository mebusw/awesome-jackyshen-skills (4 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,306 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 skills, from other repositories
llm-app-patterns
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.
prompt-optimization
Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…
enhance-prompt
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
prompt-engineer
Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot…
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.
ideogram4
Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers…