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OpenClaw Seedance Prompt Library

核心功能:按风格/主题检索Seedance提示词、优化粗糙提示、双语互转、将创意生成适配提示包、提取可复用提示逻辑。典型场景:寻求创作灵感、优化已有提示、获取多版本选项、基于模糊想法生成专业提示。输出适配需求分5种模式,如提示短名单给灵感、改写含原提示+优化版+改动说明、提示包含安全/风格化/实验型变体等,均输出精炼实用内容。

x-rayluan
x-rayluan
热度 46.18
最近更新 2026-05-11 17:39:08
分类:创作依赖:读写文件 / 联网浏览搜索 / 代码执行 / 内部调用大模型应用场景:文案创作 / 翻译 / 视频编辑 / 模板

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add openclaw-seedance-prompt-library
Metadata
name
openclaw-seedance-prompt-library
description
Search, rewrite, and generate Seedance 2.0 video prompts with cinematic variants and bilingual output. Seedance提示词检索/改写/生成

OpenClaw Seedance Prompt Library

Use this skill to turn a large prompt collection into a practical working system for prompt selection, prompt rewriting, and prompt generation.

Upstream prompt material was adapted from a public Seedance collection. Keep any required license handling at the repository level, not in the normal user-facing output flow.

Core use cases

  • Find Seedance prompt examples by style, subject, motion, or camera language
  • Rewrite a weak prompt into a stronger cinematic prompt
  • Convert Chinese prompts to English and English prompts to Chinese
  • Turn a user idea into a Seedance-ready prompt pack
  • Extract reusable prompt patterns from the library instead of copying blindly

Working model

Do not dump a giant wall of prompts.

Instead:

  1. classify the user's goal
  2. search for 3-8 relevant examples
  3. identify what actually makes them work
  4. synthesize a better prompt for the user's use case
  5. return a small, usable set of outputs

Output modes

Choose the output format that best fits the request:

1) Prompt shortlist

Use when the user wants inspiration.

Return:

  • 3-8 relevant prompt examples
  • one-line note on why each is relevant
  • optional source title / ID when available

2) Prompt rewrite

Use when the user already has a rough prompt.

Return:

  • original prompt
  • improved prompt
  • what changed: subject / motion / camera / lighting / duration / aspect ratio / pacing

3) Prompt pack

Use when the user wants multiple options.

Return 3 variants:

  • safe — closest to user's request
  • stylized — stronger cinematic/style choices
  • experimental — more ambitious motion or scene design

4) Bilingual prompt delivery

Use when the user needs Chinese + English.

Return:

  • Chinese version
  • English version
  • short note on any non-literal adaptation

5) Prompt generator

Use when the user gives only an idea, image concept, mood, or rough scene.

Return:

  • core prompt — strongest balanced version
  • safe — most reliable generation version
  • stylized — stronger visual identity and camera language
  • experimental — higher-risk, higher-novelty version
  • optional negative / avoid notes if they help reduce model drift
  • optional CN + EN pair when bilingual output helps

Prompt construction rules

When rewriting or creating prompts, prefer this structure:

  1. Subject — who / what is on screen
  2. Scene — environment and setting
  3. Action — what changes over time
  4. Camera — shot type, movement, framing
  5. Style — cinematic, anime, realistic, surreal, etc.
  6. Lighting / mood — color, atmosphere, time of day
  7. Output constraints — duration, resolution, aspect ratio if useful

If the source example is strong, extract the structure, not just the wording.

Generator workflow

When the user gives only a rough idea, generate prompts in this order:

  1. lock the subject and scene
  2. choose one dominant motion arc
  3. choose one camera logic
  4. add one style layer, not five competing ones
  5. add constraints only if they improve reliability
  6. output a core prompt first
  7. then derive safe / stylized / experimental variants

If the request is weak or underspecified, fill gaps with plausible cinematic defaults instead of asking too many questions.

Quality rules

  • Prefer specificity over adjectives spam
  • Prefer concrete motion over vague “dynamic” wording
  • Prefer camera instructions that imply visual change
  • Avoid contradictory style directions
  • Keep prompt length proportional to complexity
  • If a user asks for a simple result, do not over-engineer it

Safety notes

  • If copyright or character/IP risk is high, flag it and offer an original alternative
  • Prefer transformed prompt synthesis over verbatim copying
  • If a user wants a close clone of a known character or franchise scene, offer an adjacent original version too

References

Read these files as needed:

  • references/usage-patterns.md — how to search, adapt, and package prompts
  • references/source-attribution.md — source repo, license, and reuse rules
  • upstream dataset: https://github.com/YouMind-OpenLab/awesome-seedance-2-prompts

Optional helper scripts

  • scripts/search-seedance-readme.mjs — keyword search against upstream README prompt entries via GitHub raw URLs