full-aigc-skills/jimeng-skills

jimeng-prompt-text2video

Provides comprehensive guidance for crafting text-to-video prompts for 即梦 (Dreamina/Jimeng) video models (视频3.0 Pro, Doubao Seedance 2.0, Seedance 1.5/1.0, 智能多帧). Video prompts require two additional dimensions beyond image prompts: explicit motion description and camera movement direction. Use when the user wants to write, refine, or optimize a video generation prompt; mentions 文生视频, text2video, 视频提示词, 运镜, camera movement, 生成一段...的视频, 帮我写个视频; describes a scene t…

First seen Jul 28, 2026

Installation

$ npx skills add full-aigc-skills/jimeng-skills --skill jimeng-prompt-text2video

Summary

  • Provides comprehensive guidance for crafting text-to-video prompts for 即梦 (Dreamina/Jimeng) video models (视频3.0 Pro, Doubao Seedance 2.0, Seedance 1.5/1.0, 智能多帧).
  • Video prompts require two additional dimensions beyond image prompts: explicit motion description and camera movement direction.
  • Use when the user wants to write, refine, or optimize a video generation prompt; mentions 文生视频, text2video, 视频提示词, 运镜, camera movement, 生成一段...的视频, 帮我写个视频; describes a scene they want as a video; or provides a rough scene description to be turned into a polished video prompt.
  • This skill covers 12 video scenario categories with 35 annotated examples, a motion and camera word library, and a complete camera movement reference covering 7 basic plus 6 advanced compound techniques with emotional effect mappings.
  • Always use this skill when the user needs help writing any video generation prompt for 即梦.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

LicenseComplete terms in LICENSE.txt

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 8,840 B
  • docs SUMMARY.md 994 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 10 installs

SKILL.md

jimeng-prompt-text2video — 即梦文生视频提示词

Craft production-ready text-to-video prompts for 即梦 Dreamina video models (视频3.0 Pro, Doubao Seedance 2.0, Seedance 1.5, Seedance 1.0, 智能多帧).

When to use this skill

Use this skill when the user:

  • Asks you to write a video generation prompt ("帮我写个视频提示词")
  • Describes a scene they want as a moving image / video
  • Wants to refine or optimize an existing video prompt
  • Mentions keywords like: 文生视频, text2video, 视频生成, 视频提示词, 运镜, camera movement, Seedance
  • Asks about how to describe motion, camera work, or temporal progression in a prompt

Do NOT use this skill for:

  • Executing CLI commands to generate videos → use jimeng-cli-text2video
  • Writing image-to-video prompts → use jimeng-prompt-image2video
  • Writing text-to-image prompts → use jimeng-prompt-text2image

Model Version Guide

即梦 has multiple video model lines. The core writing approach differs by model:

Model Formula Key Difference
视频3.0 / 3.0 Pro 主体 + 动作 + 场景 + 镜头 + 风格 + (情绪演绎) + (照明) 自然语言自由书写; 支持切镜和创意特效
Doubao Seedance 2.0 系列 主体 + 动作/运动 + 空间背景/光影/风格 + 镜头调度/音效 支持T2V/I2V/R2V/V2V; 原生音频+视频联合生成; 多模态参考(图片/音频/视频); 支持文字生成(广告语/字幕/气泡台词); 支持视频编辑(元素增删改/延长/轨道补齐)
Seedance 1.5 Pro 主体 + 动作 + 场景 + 镜头 + 风格 更快的生成速度
Seedance 1.0 Pro / Pro Fast 主体 + 动作 + 场景 + 镜头 + 风格 Pro Fast: 极致速度
图生视频 (I2V) 动作 + 镜头 + (情绪/照明) 由图像提供主体+场景, 提示词只控制动态
智能多帧 [多帧图像] + [每帧时长] + [运镜提示词] 多图驱动一镜到底; 上传2-10帧; 每帧1-6s

Core Methodology

The video prompt formula extends the image formula with two critical dimensions: motion and camera.

For 视频3.0/3.0 Pro 文生视频:

主体 + 动作 + 场景 + 镜头 + 风格 + (情绪演绎) + (照明)

For 图生视频 (image-to-video):

动作 + 镜头 + (情绪/照明)

For Doubao Seedance 2.0 系列 文生视频:

主体 + 动作/运动 + 空间背景/光影/风格 + 镜头调度/音效

The key difference from text-to-image prompting:

  • Motion is mandatory: a video without motion is just a still image
  • Camera adds storytelling: how the camera moves determines the viewer's emotional experience
  • Duration shapes pacing: a 5-second clip needs different action density than a 10-second clip
  • For 视频3.0 Pro specifically: 自然语言自由书写, 核心思路是"直观表达出你想要的效果"
  • For Doubao Seedance 2.0: 支持多模态参考(图片/音频/视频), 可在提示词中用"图片1""图片2"指代参考素材

How to use this skill

Step 1: Identify video scenario category

→ Load rules/video-category-table.md to match user's request to the right category and example file

Step 2: Load reference materials

Load video vocabulary — choose by what you need:

需要什么 加载文件
人物动作、自然动态、动物动态、机械运动 video-words/motion.md
场景环境、视频画质、视频风格、氛围情绪、节奏描述 video-words/scene-style.md

Load camera movement references — choose by complexity:

需要什么 加载文件
推拉摇移跟升降 camera-basic.md
环绕、一镜到底、希区柯克、运镜情感映射 camera-advanced.md

Load reference guides:

  • references/jimeng-video-3.0-guide.md — when user mentions 视频3.0/3.0 Pro
  • references/smart-multi-frame-guide.md — when user mentions 智能多帧/多帧/一镜到底

For color descriptions, cross-reference text2image's color-library/chinese-traditional.md or gugong-384-colors.md.

Step 3: Build the prompt

→ Load rules/video-core-methodology.md for component-by-component build guide + presentation format

Step 4: Apply video writing rules

→ Load rules/video-writing-rules.md for all 10 rules (motion, camera, duration, light, model-matching, differentiation, action layers)

Step 5: Validate

→ Load rules/video-validation-checklist.md and run through all checks

Step 6 (User assessment): Evaluate prompt output

When the user provides an existing prompt output and asks for evaluation ("评估""检测命中率""看看优化方向"): → Load references/evaluation-framework.md for the systematic 6-dimension assessment methodology

Gotchas

  1. Action must be explicit — 即梦 cannot infer motion from static description. "一个人在街上" = static shot
  2. Complex interactions fail — multi-person interactions + camera movement = distortion risk
  3. Chinese camera terms work better — "镜头缓缓推近" > "dolly in slowly"
  4. Seedance quality/speed tradeoff — seedance2.0 = highest quality/slowest; fast = faster/lower quality
  5. Duration-to-action matching — 5s with 3-stage action = rushed. Match complexity to time
  6. First-time web authorization — some models require browser auth before first use
  7. Character consistency not guaranteed — same face across segments not reliable
  8. Camera + complex motion = risk — prioritize one over the other
  9. Model-prompt mismatch is the #1 output killer (Rule 8) — long descriptive prose → 视频3.0 Pro; structured short sentences → Seedance 2.0. Mismatching causes detail loss and poor generation. This is the single most common error in real usage.
  10. Action layer count by model (Rule 10) — Seedance 2.0 can't handle 4+ action layers reliably. Cap at 3. 视频3.0 Pro can handle 4-5.
  11. Multi-scheme differentiation is non-optional (Rule 9) — When providing 2+ alternatives, verify visual distinction. At least 2 dimensions must differ (运镜/动作密度/景别/节奏/场景). Similar schemes waste user's time.
  12. Light must change, not just exist (Rule 5) — "洒入" is a static snapshot. Use "缓缓流动""逐渐变亮""光影移动" to encode time passage.
  13. ⚠️ Never write hex color codes in video prompts — Same as image prompts: #RRGGBB values get rendered as text in the video frames, NOT as color instructions. Use Chinese color names only

Available Resources

Resource Description When to Load
rules/video-category-table.md 12 video scenario categories Step 1
rules/video-core-methodology.md Component-by-component build guide Step 3
rules/video-writing-rules.md 10 video-specific writing rules Step 4
rules/video-validation-checklist.md 基础+进阶+多方案校验清单 Step 5
video-words/motion.md Motion vocabulary library When writing motion descriptions
video-words/scene-style.md Scene/style/vocabulary library When describing scenes
camera-basic.md 7 basic camera movements Basic camera work needed
camera-advanced.md 7 compound moves + emotion mapping Advanced camera work
references/jimeng-video-3.0-guide.md 视频3.0/3.0 Pro: 8 dimensions User mentions 视频3.0
references/smart-multi-frame-guide.md 智能多帧: 多图一镜到底 User mentions 智能多帧/多帧
references/evaluation-framework.md 6维评估框架: 词库命中率/规则遵从度/公式完整性/模型匹配/区分度/校验 User asks to assess/evaluate skill output