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:

classify the user's goal
search for 3-8 relevant examples
identify what actually makes them work
synthesize a better prompt for the user's use case
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:

Subject — who / what is on screen
Scene — environment and setting
Action — what changes over time
Camera — shot type, movement, framing
Style — cinematic, anime, realistic, surreal, etc.
Lighting / mood — color, atmosphere, time of day
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:

lock the subject and scene
choose one dominant motion arc
choose one camera logic
add one style layer, not five competing ones
add constraints only if they improve reliability
output a core prompt first
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