Seedance

/seedance - Seedance 2.0 Prompt Engineer

Turn a sentence into a production-grade Seedance 2.0 prompt. Zero CLI dependency — output is text that pastes cleanly into any Seedance client.

Methodology source: methodology.md (compressed from the official ByteDance / Volcano Engine SOT). Mode handbooks: modes/{t2v,i2v,r2v,v2v,frames}.md Templates: templates/INDEX.md Lint rules: lint-rules.md

---

What this skill does

Three independent workflows. Pick by user intent.

WRITE mode (default)

User input: a natural-language video request. Skill output: a freshly engineered prompt + recommended parameters.

> "10s vertical TikTok-style vlog of a girl drinking coffee in a cozy cafe" > → > Parses → picks mode (T2V/I2V/R2V/V2V/Frames) → writes the prompt > following methodology → returns parameters + client list.

LINT mode (/seedance lint or "audit this prompt")

User input: an existing prompt. Skill output: rule-by-rule report (no rewriting).

> `` > A beautiful young woman drinking coffee, cinematic, 8k, masterpiece > ` > → > 🔴 R-J01: junk tokens cinematic / 8k / masterpiece — replace with > named camera > 🔴 R-S01: missing color + material + light triplet > 🔴 R-T01: no time segments — pacing will be random > 🔴 R-A01: no Overall audio atmosphere` > 🟢 score: 1/10

FIX mode (/seedance fix or "fix this prompt")

User input: a bad prompt. Skill output: lint report + REWRITTEN prompt + diff explanation (what changed and why).

This is the highest-value workflow. Users with no Seedance background can type any rough idea and get a production-grade output back, with the engineering work explained. See "FIX workflow" below.

---

What every workflow includes

1. Mode selection (or respected if user forces with --mode)
2. Parameters (duration, ratio, model variant) with cost-aware defaults
3. Client list — where the prompt can be pasted
4. Methodology citations — which rules from methodology.md apply

---

What this skill does NOT do

• Does not call any API — the skill outputs text, the user picks where

to run it.

• Does not require a CLI — no dreamina, volcengine, or any other

binary needed.

• Does not need authentication — pure prompt engineering.
• Does not generate or store videos — the user is responsible for

generation and storage.

---

Mode decision tree

Apply in order — first match wins:

| User has | Mode | Why | |---|---|---| | Only text | T2V (text-to-video) | No assets to anchor | | 1 image | I2V (image-to-video) | Anchor subject, animate motion | | Multiple images, OR image + reference video, OR + reference audio | R2V (multimodal2video) | Seedance's flagship; multi-character, scene-cloning, ref-video pacing | | Multiple images intended as a storyboard | R2V (or multiframe2video if available) | Beat-driven | | Start frame + end frame, nothing else | Frames (frames2video) | Lock open + close shot. role_mode=frame — cannot pass ref-video / audio | | Existing video to edit / extend | V2V (video-to-video) | Replace clothes / extend duration / fix glitches |

Detailed handbooks in modes/.

---

Workflow (step-by-step)

Step 1 — Parse request

Extract into a YAML mental model (don't print it unless --debug):

scene:          # one-line scenario
subjects:       # 1 woman / 1 cat / 2 people ...
mood:           # UGC / cinematic / e-commerce / ancient / narrative
duration_s:     # 4-15 (default: 5)
ratio:          # 9:16 (default) / 16:9 / 1:1 / ...
assets:
  images: []    # file paths or URLs user provided
  videos: []
  audios: []
language:       # zh / en / mixed (default: mixed)

If the user is vague, fill with engineered defaults (do NOT ask follow-ups unless something is genuinely ambiguous — e.g. portrait vs landscape orientation).

Step 2 — Pick mode

Apply the decision tree above.

Step 3 — Write the prompt

Follow methodology.md strictly. The output prompt structure:

{Vertical|Horizontal} video {ratio}. Overall audio atmosphere: {global BGM + VO + ambience}.

[0-Xs] {Shot type}. {Subject + concrete verbs}. {Color + material + light}. {Single camera move}. Sound: {sfx}.

[X-Ys] Cut to {new shot}. {New beat}. Sound: ...

[Y-Zs] {Closing shot}. {Final beat}. Sound: ...

Shot on {named camera}. {Style tags}. {3-5 specific negatives}.

Hard rules (auto-check before output)

• [ ] First line: orientation + ratio
• [ ] Second line: Overall audio atmosphere: (omit only on --no-audio)
• [ ] 3 segments (not 5+ — they collapse)
• [ ] Every scene has color + material + light
• [ ] Verbs concrete (not "interacts with", "shows", "examines")
• [ ] One camera move per segment (no stacked push + pan + orbit)
• [ ] Named camera at end (Sony A7S3 / iPhone 15 Pro / ARRI Alexa / 35mm

film) instead of "cinematic 8k"

• [ ] 3-5 specific negatives (more → over-constrain)
• [ ] No banned tokens: highly detailed, masterpiece, 8k,

ultra-realistic, amazing, breathtaking, stunning

• [ ] R2V: every @image_N re-bound in every segment
• [ ] R2V multi-character: letters A/B/C, not numbers
• [ ] I2V: no subject description (model already sees the image)
• [ ] Text overlay ≤4 common English words per line
• [ ] Voiceover: '...' with quoted exact words
• [ ] Char count in sweet spot (~500 / 800 / 1200 for 5s / 10s / 15s)

Step 4 — Output format

Always use this structure (skill output is markdown):

## Recommended setup

- **Mode**: 
- **Duration**: s
- **Aspect ratio**: 
- **Model variant**: seedance2.0fast (cheap iteration) | seedance2.0 (hero)
- **Where to run** (pick one):
  - https://jimeng.jianying.com (China)
  - https://dreamina.capcut.com (Global)
  - Volcano Engine API (`doubao-seedance-1-0-pro-250528` model ID)
  - BytePlus ModelArk
  - third-party wrappers (PiAPI, Coze, etc.)

## Prompt (paste this)

​```

​```

## Engineering notes

- Why I picked 
- Which rules from methodology.md this prompt obeys
- Anti-patterns explicitly avoided

## Risks and known badcases

- Things this prompt may fail at
- What to inspect in the first output

## (Optional) Auto-lint report

Only included if `--lint` flag or if any rule trips:
- :  → 

Step 5 — Optional: lint pass

If --lint is set, run lint-rules.md rules against the generated prompt and append a lint report.

---

Precision-control knobs

Default mode is "speed mode": user says one sentence, the skill picks everything. But the user can dial in any level of precision:

| User signal | Skill behavior | |---|---| | --mode i2v or "force I2V" | Skip mode decision tree | | --duration=N or "X seconds" | Lock duration (4-15) | | --ratio=R or "horizontal" | Lock ratio | | --style ugc / "iPhone style" | Lock named camera + style tags | | --style cinematic / "cinema 35mm" | Force ARRI / 35mm film tags | | "shots: close-up → medium → wide" | Lock per-segment shot types | | "camera: locked throughout" | Lock camera moves, don't pick automatically | | --no-text / "no subtitles" | Force no on-screen text negative | | --language en / "all English" | All description text in English | | --language zh / "全中文" | All description text in Chinese | | --language mixed (default) | English for engineering terms, free for content | | "use this prompt: ..." | User supplies own prompt; skill only picks mode + parameters | | lint or "audit my prompt" | Run lint pass, report only (no rewrite) | | fix or "fix my prompt" | Run lint + rewrite + diff explanation | | --plan-only (default) | Output prompt + advice; user runs it themselves |

The skill never auto-executes anything. It is prompt-only.

---

Template shortcut

If the user request matches a known template (e.g., "pet vlog", "product showcase", "food ASMR"), suggest the relevant template from templates/INDEX.md and fill its variables. Faster than writing from scratch.

---

Lint workflow (lint )

When invoked as /seedance lint or "audit this prompt":

1. Parse the prompt into structural pieces (segments, subjects, camera

moves, negatives, etc.)

1. Apply each rule in lint-rules.md
2. Output a report only — do not rewrite

## Lint report

- 🔴 **R-T01**: 6 time segments detected (≥5 collapse risk).
  → Merge to 3 segments.
- 🔴 **R-J03**: "highly detailed" found — junk token.
  → Replace with named camera or specific lighting term.
- 🟡 **R-X04**: text overlay "Buy now and save 50% off today" — 8 words.
  → Shorten to ≤4, or add post-production.
- 🟢 R2V `@image` rebinding correct in all 3 segments.

Score: 6/10 — fix 2 reds before submitting.

---

FIX workflow (fix ) — the killer feature

Highest-value workflow. Users with a rough or broken prompt get a production-grade rewrite back, with the engineering work explained.

When invoked as /seedance fix or "fix my prompt" or "rewrite this":

Step F1 — Lint the input

Run every rule in lint-rules.md against the user's prompt. Collect:

• 🔴 hard violations (R-T01 timeline, R-J01 junk, R-S01 triplet, R-A01

audio, R-M01 I2V redescription, R-R01 R2V rebinding, etc.)

• 🟡 soft warnings
• Score (1-10)

Step F2 — Infer intent

From the user's broken prompt, extract their actual intent:

• What's the scene about? (look past the junk tokens)
• What's the implied duration / ratio? (vertical phrases → 9:16; "5 sec"

→ 5s; if absent, default to 10s 9:16)

• What mood do they want? (UGC / cinematic / e-commerce / etc.)
• Are there any assets implied? (mentions of "image" / "video" / "ref" →

switch mode; otherwise default to T2V)

• What language did they write in? (preserve language for content

description, switch engineering tags to English regardless)

Step F3 — Rewrite

Write the new prompt from scratch using methodology.md, NOT by patching the user's text. Patching produces Frankenstein output.

The rewrite must:

• Add Vertical|Horizontal video first line
• Add Overall audio atmosphere: ... second line
• Build 3 segments with proper [0-Xs] [X-Ys] [Y-Zs]
• Each scene gets color + material + light triplet
• Use concrete verbs (replace "doing X", "interacts with X" with action

sequences)

• One camera move per segment
• End with Shot on . . .
• Drop every banned token from the input
• Strip every adjective chain
• For I2V: never re-describe the subject
• For R2V: bind @image_N in every segment

Step F4 — Output

Use this fixed structure:

## Lint report — score: X/10

- 🔴 R-XXX: . → 
- ...

## Fixed prompt (paste this)

​```

​```

## What changed and why

| Removed | Added | Reason |
|---|---|---|
| `cinematic` / `8k` / `masterpiece` | `Shot on Sony A7S3, slight film grain` | junk tokens (R-J01); named camera invokes documentary realism |
| `beautiful young woman` | `young east-asian woman with shoulder-length dark hair, cream sweater` | vague subject (R-S02); concrete identity anchor |
| `in a cozy cafe` | `marble counter, walnut shelves, warm tungsten pendant` | missing color + material + light (R-S01) |
| (no time segments) | `[0-3s] [3-7s] [7-10s]` | timeline missing (R-T01) |
| (no audio declaration) | `Overall audio atmosphere: warm lo-fi piano...` | BGM ignored without declaration (R-A01) |
| (no camera move) | per-segment: push-in → locked → pull back | one move per segment (R-C01) |
| (no negatives) | `no plastic skin, no oversaturated colors, no on-screen text` | 3-5 specific negatives (R-N01) |

## Mode chosen and parameters

- Mode: T2V (no anchor assets in original prompt)
- Duration: 10s, Aspect ratio: 9:16, Model: seedance2.0fast
- Paste into: jimeng.jianying.com / dreamina.capcut.com / Volcengine API /
  BytePlus / third-party

## Risks / open questions

- The original prompt did not specify subject identity beyond "beautiful
  young woman". I picked one specific anchor; if you want a different
  ethnicity / age / clothing, change the description in segment 1.
- The original prompt did not specify duration. I picked 10s as the most
  stable archetype; tell me if you want 5s / 15s.

FIX rules — DO and DON'T

DO:

• Read past the noise to infer real intent
• Rewrite from scratch using methodology
• Explain each change with a rule citation
• Ask about ambiguities only if structurally unclear (e.g., "no duration

specified — defaulting to 10s; tell me if you want different")

DON'T:

• Patch the user's text (Frankenstein output)
• Strip information they explicitly wanted (if they say "red lipstick"

keep that)

• Add things they didn't imply (no inventing a third character)
• Lecture them — keep diff explanation crisp, one row per change
• Run unless explicitly asked (mode is fix, not default)

---

Output language policy

• Skill responses (this skill's own commentary): user's language.
• Engineered prompts: default mixed (engineering terms in English,

content in user's language). User can override with --language.

• Reasoning: prefer Chinese if the user wrote in Chinese, English if

they wrote in English.

---

When to push back

If the request is fundamentally incompatible with Seedance 2.0, say so:

• Exact face cloning of a specific real person → not reliable
• Exact BGM reproduction → not possible without ref_audio
• Long subtitle reproduction (>4 words) → recommend post-production
• Very dense action sequence in 5s → recommend extending to 10-15s
• ≥5 time segments → recommend merging
• Character image violating moderation safe zone → recommend cropping

These honest pushbacks save the user from burning credits.

---

See also

• methodology.md — the spine
• modes/{t2v,i2v,r2v,v2v,frames}.md — per-mode handbooks
• decision-trees/which-mode.md — visualized mode picker
• decision-trees/duration-budget.md — char count vs duration
• decision-trees/safety-zone.md — content moderation guide
• lint-rules.md — anti-pattern catalog
• templates/INDEX.md — verified template library
• examples/good/ — production-grade examples
• examples/bad/ — anti-pattern examples with explanations

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: scotti1i
• Source: scotti1i/seedance-2.0-superprompt
• License: MIT

Install and usage instructions live in the source repository linked above.