# Seedance > Seedance 2.0 prompt engineer. Three modes: WRITE (natural language → production-grade prompt), LINT (diagnose anti-patterns in existing prompt), FIX (auto-rewrite a bad prompt into a good one with diff explanation). Auto-picks T2V/I2V/R2V/V2V/Frames, enforces eight-element formula, three-segment timeline, @-syntax, named cameras, and negative constraints. Output pastes cleanly into ANY Seedance c… - **Type:** Skill - **Install:** `agentstack add skill-scotti1i-seedance-2-0-superprompt-seedance` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [scotti1i](https://agentstack.voostack.com/s/scotti1i) - **Installs:** 0 - **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [scotti1i](https://github.com/scotti1i) - **Source:** https://github.com/scotti1i/seedance-2.0-superprompt/tree/main/seedance ## Install ```sh agentstack add skill-scotti1i-seedance-2-0-superprompt-seedance ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # /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`): ```yaml 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): ```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.) 2. Apply each rule in `lint-rules.md` 3. Output a report only — **do not rewrite** ```markdown ## 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: ```markdown ## 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](https://github.com/scotti1i) - **Source:** [scotti1i/seedance-2.0-superprompt](https://github.com/scotti1i/seedance-2.0-superprompt) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-scotti1i-seedance-2-0-superprompt-seedance - Seller: https://agentstack.voostack.com/s/scotti1i - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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